This paper aims at challenging Bernstein's problem called the "Degrees-of-Freedom problem," which remains unsolved from both the physiological and robotics viewpoints. More than a half century ago A.N. Bernstein observed that "dexterity" residing in human limb motion emerges from accumulated involvement of multi-joint movements in surplus DOF. It is also said in robotics that redundancy of DOFs in robot mechanisms may contribute to enhancement of dexterity and versatility. However, kinematic redundancy incurs a problem of ill-posedness of inverse kinematics from task-description space to joint space. In the history of robotics research such ill-posedness problem of inverse-kinematics has not yet been attacked directly but circumvented by introducing an artificial performance index and determining uniquely an inverse kinematics solution by minimizing it. Instead of it, this paper introduces two novel concepts named "stability on a manifold" and "transferability to a submanifold" in treating the case of human multi-joint movements of reaching and shows that a sensory feedback from task space to joint space together with a set of adequate dampings enables any solution to the overall closed-loop dynamics to converge naturally and coordinately to a lower-dimensional manifold describing a set of joint states fulfilling a given motion task. This means that, without considering any type of inverse kinematics, the reaching task can be accomplished by a sensory feedback with adequate choice of a stiffness parameter and damping coefficients. It is also shown that these novel concepts can cope with annoying characteristics called "variability" of redundant joint motions seen typically in human skilled reaching. Finally, it is pointed out that the proposed control signals can be generated in a feedforward manner in case of human limb movements by referring to mechano-chemical characteristics of activation of muscles. Based on this observation, generation of human skilled movements of reaching can be interpreted in terms of the proposed "Virtual-Spring" hypothesis instead of the traditional "Equilibrium-Point" hypothesis.

There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.

This paper is devoted to the problem of force sensorless disturbance rejection in robot manipulators. In the proposed approach, the control system uses position sensor signals and estimated values of external forces, instead of force sensor signals. The estimation process is performed via an adaptive force estimator. Then the estimated force vector is utilized to compensate for the force disturbance effect in order to achieve a better trajectory tracking performance. The force estimation is carried out directly using no environment model. Asymptotical stability of the proposed control system is analyzed by the invariant set and Lyapunov direct method establishing an appropriate theorem. Finally, the performance of the proposed control system is verified using numerical simulation.

The authors propose a system for searching the shape of human hands and fingers in real time and with high accuracy, without using any special peripheral equipment such as range sensor, PC cluster, etc., by a method of retrieving similar image quickly with high accuracy from a large volume of image database containing the complicated shapes and self-occlusions. In designing the system, we constructed a database in a way to be adaptable even to differences among individuals, and searched CG images of hand similar to unknown hand image, through extraction of characteristics using high-order local autocorrelational patterns, reduction of the amount of characteristics centering on principal component analysis, and prior rearrangement of data corresponding to the amount of characteristics. As a result of experiments, our system performed high-accuracy estimation of human hand shape where mean error was 7 degrees in finger joint angles, with the processing speed of 30 fps or over.

Limit cycle oscillations of rotor speed are substantially caused by inverter's dead time, when an induction motor (IM) drive operates in low frequency condition. In this paper, without any hardware modification, discontinuous PWM (DPWM3) modulate strategy possibly controls the unfavorable rotor speed limit cycle under no load operation condition. Simulated results are presented to demonstrate the effectiveness.

This paper deals with new fuzzy controller for handling systems having large dead time and nonlinearities, via approximations of large rule fuzzy logic controller by simplest fuzzy controller (4 rules). The error between large rule fuzzy controller and simplest fuzzy controller are compensated by proposed compensating factors. These compensating factors are modified to handle large dead time and nonlinear systems. Features of proposed approximations are discussed. The concept of variation of nonlinearity factor of fuzzy controller is also discussed. Various processes from different literatures are utilized to demonstrate the proposed methodology. After doing many simulations it has been found that with proper tuning, overall system handles large dead time and nonlinearity which may be difficult by conventional methods. The processes are also simulated for load disturbances and change of operating point (set point) and it has been found that proposed scheme is robust for long dead times.

In this paper we are concerned with designing an extremum seeking control law for nonlinear systems. This is a modification of a standard extremum seeking controller. It is equipped with an accelerator to the original one aimed at achieving the maximum operating point more rapidly. This accelerator is designed by making use of a polynomial identification of an uncertain output map, the Butterworth filter to smoothen the control, and analog-digital converters. Numerical experiments show how this modified approach can be well in control of the Monod model of bioreactors.

This paper presents a novel method of structure selection and identification for Hammerstein type nonlinear systems. An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The connection coefficients of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. The adjusting parameters for the ACF model structure, i.e. the number and widths of the subdomains and the shape of the ACF are properly selected by using a genetic algorithm, in which the Akaike information criterion is utilized as the fitness value function. The effectiveness of the proposed method is confirmed through numerical experiments.

Variable-coefficient generalizations of integrable nonlinear equations are one of exciting subjects in the study of mechanical, physical, mathematical and engineering sciences. In this paper, we present a KdV family (namely, KdV, modified KdV, Calogero-Degasperis-Fokas and Harry-Dym equations) with variable coefficients in (2 + 1) dimensions.

Finding DC operating points of nonlinear circuits is an important problem in circuit simulation. The Newton-Raphson method employed in SPICE-like simulators often fails to converge to a solution. To overcome this convergence problem, homotopy methods have been studied from various viewpoints. There are several types of homotopy methods, one of which succeeded in solving bipolar analog circuits with more than 20000 elements with the theoretical guarantee of global convergence. In this paper, we propose an improved version of the homotopy method that can find DC operating points of practical nonlinear circuits smoothly and efficiently. Numerical examples show the effectiveness of the proposed method.

In deep submicron designs, the interconnect wires play a major role in the timing behavior of logic gates. The effective capacitance C_eff concept is usually used to calculate the delay of gate with interconnect loads. In this paper, we present a new method of Integration Approximation to calculate C_eff. In this new method, the complicated nonlinear gate output is assumed as a piecewise linear (PWL) waveform. A new model is then derived to compute the value of C_eff. The introduction of Integration Approximation results in C_eff being insensitive to output waveform shape. Therefore, the new method can be applied to various output waveforms of CMOS gates with RC-π loads. Experimental results show a significant improvement in accuracy.

In this paper the spectral density of the additive jitter noise in continuous time (CT) Delta-Sigma modulators (DSM) is derived analytically. Making use of the analytic results, extracted in this paper, a novel method for elimination of the damaging effects of the clock jitter in continuous time Delta-Sigma modulators is proposed. In this method instead of the conventional waveforms used in the feedback path of CT DSM's such as the non return to-zero, the return to-zero, and the half delay return to-zero, an impulse waveform is employed.

A new impulse noise detection algorithm is presented, which can successfully remove impulse noise from corrupted images while preserving image details. The impulse detection algorithm is combined with median filtering to achieve noise removal. The main advantage of the proposed algorithm is that it can detect the impulse noise with high accuracy while reducing the probability of detecting image details as impulses. Also, it can be applied iteratively to improve the quality of restored images. It is efficient and low in complexity. Furthermore, it requires no previous training. Extensive experimental results show that the proposed approach significantly outperforms many well-known techniques.

A new detection methodology for both of the core and the delta of the fingerprint using the extended relational graph is presented. This paper shows the way to detect both of the core loop and the delta loop from the extended relational graph, which we proposed in order to summarize the global feature of the fingerprint ridge pattern distribution. The experimental results for 180 fingerprint samples show that the processing time is ranging from 0.34 [sec] to 0.44 [sec] for each fingerprint image by using Pentium 4 1.8 GHz Processor. In our experiments, the core and the delta were successfully extracted in 94.4% of the 180 samples.

Though block-based motion estimation techniques are primarily designed for video coding applications, they are increasingly being used in other video analysis applications due to their simplicity and ease of implementation. The major drawback associated with these techniques is that noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors. Similar noises may further be introduced when the technique of global motion compensation is applied to obtain true object motion from video sequences where both the camera and object motions are present. This paper presents a new technique for capturing large number of true object motion vectors by eliminating the false motion vector fields, for use in the application of object motion based video indexing and retrieval applications. Experimental results prove that our proposed technique significantly increases the percentage of retained true object motion vectors while eliminating all false motion vectors for variety of standard and non-standard video sequences.

This paper proposes homogeneous neural networks (HNNs), in which each neuron has identical weights. HNNs can realize shift-invariant associative memory, that is, HNNs can associate not only a memorized pattern but also its shifted ones. The transition property of HNNs is analyzed by the statistical method. We show the probability that each neuron outputs correctly and the error-correcting ability. Further, we show that HNNs cannot memorize over the number,, of patterns, where m is the number of neurons and k is the order of connections.

The lifting scheme is an efficient and flexible method for the construction of linear and nonlinear wavelet transforms. In this paper, a novel lossless image coding technique based on the lifting scheme using discrete-time cellular neural networks (DT-CNNs) is proposed. In our proposed method, the image is interpolated by using the nonlinear interpolative dynamics of DT-CNN, and since the output function of DT-CNN works as a multi-level quantization function, our method composes the integer lifting scheme for lossless image coding. Moreover, the nonlinear interpolative dynamics by A-template is used effectively compared with conventional CNN image coding methods using only B-template. The experimental results show a better coding performance compared with the conventional lifting methods using linear filters.

The requirement for achieving the smoothness of mode transit between track seeking and track following has become a challenging issue for hard disk drive (HDD) motion control. In this paper, a random-optimization-based self-organizing neuro-fuzzy controller (RO-SNFC) for HDD servo system is presented. The proposed controller is composed of three designs. First, the concept of pseudo-errors is used to detect the potential dynamics of the unknown plant for rule extraction. Second, the propensity of the obtained pseudo-errors is specified by a cubic regression model, with which the cluster-based self-organization is implemented to generate clusters. The generated clusters are regarded as the antecedents of the T-S fuzzy "IF-THEN" rules. The initial knowledge base of the RO-SNFC is established. Third, the well-known random optimization (RO) algorithm is used to evolve the controller parameters for control efficiency and robustness. In this paper, a motion reference curve for HDD read/write head is employed. With the reference velocity curve, the RO-SNFC is used to achieve the optimal positioning control. From the illustrations, the feasibility of the proposed approach for HDD servo systems is demonstrated. Through the comparison to other approaches, the excellent performance by the proposed approach in access time and positioning smoothness is observed.

This paper deals with the use of neural network rule extraction techniques based on the Genetic Programming (GP) to build intelligent and explanatory evaluation systems. Recent development in algorithms that extract rules from trained neural networks enable us to generate classification rules in spite of their intrinsically black-box nature. However, in the original decompositional method looking at the internal structure of the networks, the comprehensive methods combining the output to the inputs using parameters are complicated. Then, in our paper, we utilized the GP to automatize the rule extraction process in the trained neural networks where the statements changed into a binary classification. Even though the production (classification) rule generation based on the GP alone are applicable straightforward to the underlying problems for decision making, but in the original GP method production rules include many statements described by arithmetic expressions as well as basic logical expressions, and it makes the rule generation process very complicated. Therefore, we utilize the neural network and binary classification to obtain simple and relevant classification rules in real applications by avoiding straightforward applications of the GP procedure to the arithmetic expressions. At first, the pruning process of weight among neurons is applied to obtain simple but substantial binary expressions which are used as statements is classification rules. Then, the GP is applied to generate ultimate rules. As applications, we generate rules to prediction of bankruptcy and creditworthiness for binary classifications, and the apply the method to multi-level classification of corporate bonds (rating) by using the financial indicators.

In this paper, we shall construct mathematical theory based on the concept of set-valued mappings, suitable for available operation of extraordinarily complicated large-scale network systems by introducing some connected-block structures. A fine estimation technique for availability of system behaviors of such network systems are obtained finally in the form of fixed point theorem for a special system of fuzzy-set-valued mappings.

We present an efficient method to optimize network resource allocations under nonlinear Quality of Service (QoS) constraints. We first propose a suite of generalized proportional allocation schemes that can be obtained by minimizing the information-theoretic function of relative entropy. We then optimize over the allocation parameters, which are usually design variables an engineer can directly vary, either for a particular user or for the worst-case user, under constraints that lower bound the allocated resources for all other users. Despite the nonlinearity in the objective and constraints, we show this suite of resource allocation optimization can be efficiently solved for global optimality through a convex optimization technique called geometric programming. This general method and its extensions are applicable to a wide array of resource allocation problems, including processor sharing, congestion control, admission control, and wireless network power control.

Information processing with only locally connected networks such as cellular neural networks is advantageous for integrated circuit implementations. Adding long range connections can often enhance considerably their performance. It is sufficient to activate these connections randomly from time to time (blinking connections). This can be realized by sending packets on a communication network underlying the information processing network that is needed anyway for bringing information in and out of the locally connected network. We prove for the case of multi-stable networks that if the long-range connections are switched on and off sufficiently fast, the behavior of the blinking network is with high probability the same as the behavior of the time-averaged network. In the averaged network the blinking connections are replaced by fixed connections with low (average) coupling strength.

The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.

Some statistical analyses of modulo-2 added binary sequences are generalized to modulo-p added p-ary sequences. First, we theoretically evaluate statistics of sequences obtained by modulo-p addition of two general p-ary random variables. Next, we consider statistics of modulo-p added chaotic p-ary sequences generated by a class of one-dimensional chaotic maps.

We study asynchronous SSMA communication systems using binary spreading sequences of Markov chains and prove the CLT (central limit theorem) for the empirical distribution of the normalized MAI (multiple-access interference). We also prove that the distribution of the normalized MAI for asynchronous systems can never be Gaussian if chains are irreducible and aperiodic. Based on these results, we propose novel theoretical evaluations of bit error probabilities in such systems based on the CLT and compare these and conventional theoretical estimations based on the SGA (standard Gaussian approximation) with experimental results. Consequently we confirm that the proposed theoretical evaluations based on the CLT agree with the experimental results better than the theoretical evaluations based on the SGA. Accordingly, using the theoretical evaluations based on the CLT, we give the optimum spreading sequences of Markov chains in terms of bit error probabilities.

In this paper, it is proved that there is a transformation between two types of nonlinear feedback shift register which can be regarded as implementation of the Bernoulli and tent maps with finite precision. This transformation can be interpreted as a sort of finite dimension version of topological conjugation between the Bernoulli and tent maps on continuous phase space. Several properties of periodic sequences generated from extended NFSRs are derived from the relation.

We define discretized Markov transformations and find an algorithm to give the number of maximal-period sequences based on discretized Markov transformations. In this report, we focus on the discretized dyadic transformations and the discretized golden mean transformations. Then we find an algorithm to give the number of maximal-period sequences based on these discretized transformations. Moreover, we define a number-theoretic function related to the numbers of maximal-period sequences based on these discretized transformations. We also introduce the entropy of the maximal-period sequences based on these discretized transformations.

Multi-swing trajectories, which refer to those trajectories which oscillate several cycles and then become unbounded, has been a nuisance in general simulation programs for power system stability study since the corresponding transient stability is very difficult to access accurately. In this letter, two possible models are developed to explain possible scenarios of such multi-swing behaviors. Theoretical investigation has strongly indicated a close relationship between multi-swing instability problems and chaotic behaviors of the power system.

In this letter, we propose a sample and hold circuit (S/H circuit) with the clock boost technique and the input signal tracking technique. The proposed circuit block generates the clock with the amplitude of V_DD + v_in, and the clock is used to control the MOS switch. By applying this circuit to a S/H circuit, we can deal with the rail-to-rail signal with maintaining low distortion. Furthermore, the hold error caused by the charge injection and the clock feedthrough can be also reduced by using the dummy switch. The Star-HSPICE simulation results are reported in this letter.

We present a new method to detect weak linear frequency modulated (LFM) signals in strong noise using the chaos oscillator. Chaotic systems are sensitive to specific signals yet immune to noise. With our new method we firstly use the Radon-Wigner transform to dechirp the LFM signal. Secondly, we set up a chaotic oscillator sensitive to weak signals based on the Duffing equation, and poising the system at its critical state. Finally, we input the dechirped sequence into the system as a perturbation of the driving force. A weak signal with the same frequency will lead to a qualitative transition in the system state. The weak signal in the presence of strong noise can then be detected from the phase transition of the phase plane trajectory of the chaotic system. Computer simulation results show that LFM signals with an SNR lower than -27 dB can be detected by this method.

Wired CDMA interface with adaptivity for interconnect capacitances is designed to receive transmitted data even under a wide variety of connection topologies. The variable gain amplifier (VGA) is one of key circuit blocks to realize the adaptivity for interconnect capacitances. The system level numerical simulations derive the VGA specifications that the required VGA gain range is from 0.37 to 2.0, which can be realized easily using a multiple-differential-pair technique.

In 1996, Sipser and Spielman [12] constructed a family of linear-time decodable asymptotically good codes called expander codes. Recently, Barg and Zemor [2] gave a modified construction of expander codes, which greatly improves the code parameters. In this paper we present a new simple algebraic decoding algorithm for the modified expander codes of Barg and Zemor, and give a Justesen-type construction of linear-time decodable asymptotically good binary linear codes that meet the Zyablov bound.

We research on an importance sampling (IS) simulation to estimate a low error probability of turbo codes. The simulation time reduction in IS depends on another probability density function (p.d.f.) called simulation p.d.f. The previous IS simulation method can not evaluate the error probability on the low SNR and waterfall region. We derive the optimal simulation p.d.f. which gives the perfect estimator. A new simulation p.d.f. design, which is related to the optimal one, is proposed to overcome the problem of the previous IS method. The proposed IS simulation can evaluate all possible error patterns. Finally, some computer simulations show that the proposed method can evaluate the error probability on the low SNR, waterfall, and error floor regions. At the evaluation of the BER of 10^-7, the simulation time of the proposed method is about ¹/350 times as short as that of the Monte-Carlo simulation. When the BER is less than 710^-8, the proposed method requires shorter simulation time than the conventional IS method.

The reliability-based heuristic search methods for maximum likelihood decoding (MLD) generate test error patterns (or, equivalently, candidate codewords) according to their heuristic values. Test error patterns are stored in lists and its space complexity is crucially large for MLD of long block codes. Based on the decoding algorithms both of Battail and Fang and of its generalized version suggested by Valembois and Fossorier, we propose a new method for reducing the space complexity of the heuristic search methods for MLD including the well-known decoding algorithm of Han et al. If the heuristic function satisfies a certain condition, the proposed method guarantees to reduce the space complexity of both the Battail-Fang and Han et al. decoding algorithms. Simulation results show the high efficiency of the proposed method.

We propose a new class of binary nonlinear codes of constant weights derived from a permutation representation of a group that is given by a combinatorial definition such as Cayley graphs of a group. These codes are constructed by the following direct interpretation method from a group: (1) take one discrete group whose elements are defined by generators and their relations, such as those in the form of Cayley graphs; and (2) embedding the group into a binary space using some of their permutation representations by providing the generators with realization of permutations of some terms. The proposed codes are endowed with some good characteristics as follows: (a) we can easily learn information about the distances of the obtained codes, and moreover, (b) we can establish a decoding method for them that can correct random errors whose distances from code words are less than half of the minimum distances achieved using only parity checking procedures.

In this paper, we explicitly formulate the average weight and the stopping set distributions and their asymptotic exponents of two-edge type LDPC code ensembles. We also show some characteristics such as the symmetry and the conditions for zero of the weight distributions of two code ensembles. Further we investigate the relation between two code ensembles from the perspectives of the weight and stopping set distributions.

Some cryptographic schemes based on the bilinear pairings were proposed recently. In this paper, we apply the pairings on elliptic curve and Elliptic Curve Cryptography to the key agreement of dynamic peer group. Each member performs authentication and contributes a secret data to negotiate a group common key by means of a binary key tree. The proposed protocol does not need a dedicated central server to perform the key agreement, and the overhead is distributed among the group members. To provide a secure dynamic group communication, the key renewing mechanism has to be included. While the member joins/leaves, the group session key will be renewed to provide the backward/forward privacy, respectively. The key renewing is much efficient because it is only confined to the keys of the key-path. The proposed protocol is flexible while the change of membership is frequent.

Though there are intensive researches on off-line electronic cash (e-cash), the current computer network infrastructure sufficiently accepts on-line e-cash. The on-line means that the payment protocol involves with the bank, and the off-line means no involvement. For customers' privacy, the e-cash system should satisfy unlinkability, i.e., any pair of payments is unlinkable w.r.t. the sameness of the payer. In addition, for the convenience, exact payments, i.e., the payments with arbitrary amounts, should be also able to performed. In an existing off-line system with unlinkable exact payments, the customers need massive computations. On the other hand, an existing on-line system does not satisfy the efficiency and the perfect unlinkability simultaneously. This paper proposes an on-line system, where the efficiency and the perfect unlinkability are achieved simultaneously.

Guess-and-Determine (GD) attacks have recently been proposed for the effective analysis of word-oriented stream ciphers. This paper discusses GD attacks on clock-controlled stream ciphers, which use irregular clocking for a non-linear function. The main focus is the analysis of irregular clocking for GD attacks. We propose GD attacks on a typical clock-controlled stream cipher AA5, and calculate the process complexity of our proposed GD attacks. In the attacks, we assume that the clocking of linear feedback shift registers (LFSRs) is truly random. An important consideration affecting the practicality of these attacks is the question of whether these assumptions are realistic. Because in practice, the clocking is determined by the internal states. We implement miniature ciphers to evaluate the proposed attacks, and show that they are applicable. We also apply the GD attacks to other clock controlled stream ciphers and compare them. Finally, we discuss some properties of GD attacks on clock-controlled stream ciphers and the effectiveness of the clock controllers. Our research results contain information that are useful in the design of clock-controlled stream ciphers.

This paper focuses on developing a square root (SQRT) algorithm in finite fields GF(p^2d) (d 0). Examining the Smart algorithm, a well-known SQRT algorithm, we can see that there is some computation overlap between the Smart algorithm and the quadratic residue (QR) test, which must be implemented before a SQRT computation. It makes the Smart algorithm inefficient. In this paper, we propose a new QR test and a new SQRT algorithm in GF(p^2d), in which not only there is no computation overlap, but also most of computations required for the proposed SQRT algorithm in GF(p^2d) can be implemented in the corresponding subfields GF(p2^d-i) for 1 i d, which yields many reductions in the computational time and complexity. The computer simulation also shows that the proposed SQRT algorithm is much faster than the Smart algorithm.

Digital fingerprinting schemes are cryptographic methods deterring buyers from illegally redistributing digital contents. It enables sellers to identify the traitor by providing each buyer with a slight different version. What is important in designing fingerprinting scheme is to make it more practical and efficient. Recently, two oblivious transfer protocol-based schemes to consider practicality were proposed. These are significant in the sense that they are completely specified from a computation point of view and are thus readily implementable. But these schemes cannot offer the security of sellers and buyers. In this paper, we show how to break the existing oblivious transfer-based fingerprinting schemes and then suggest how to make secure fingerprinting schemes against the dishonesty of sellers and buyers. We use oblivious transfer protocol with two-lock cryptosystem to make it practical and secure. All computations are performed efficiently and the security degree is strengthened in our proposal.

This paper clarifies a necessary condition and a sufficient condition for transmissibility for a given set of general sources and a given general broadcast channel. The approach is based on the information-spectrum methods introduced by Han and Verdu. Moreover, we consider the capacity region of the general broadcast channel with arbitrarily fixed error probabilities if we send independent private and common messages over the channel. Furthermore, we treat the capacity region for mixed broadcast channel.

Prediction of actual symbol probability is crucial for statistical data compression that uses arithmetic coder. Krichevsky-Trofimov (KT) estimator has been a standard predictor and applied in CTW or FWCTW methods. However, KT-estimator performs poorly when non occurring symbols appear. To rectify this we proposed a zero-redundancy estimator, especially with a finite window(Rashid and Kawabata, ISIT2003) for non stationary source. In this paper, we analyze the zero-redundancy estimators in the case of Markovian source and give an asymptotic evaluation of the redundancy. We show that one of the estimators has the per symbol redundancy given by one half of the dimension of positive parameters divided by the window size when the window size is large.

Currently, the automatic image inpainting methods emphasize the inpainting techniques either globally or locally. They didn't consider the merits of global and local techniques to compensate each other. On the contrary, the artists fixed an image in global view firstly, and then focus on the local features of it, when they repaired it. This paper proposes a progressive processing of image inpainting method based on multi-resolution analysis. In damaged and defective area, we imitate the artistic techniques to approach the effectiveness of image inpainting in human vision. First, we use the multi-resolution characteristics of wavelet transform, from the lowest spatial-frequency layer to the higher one, to analyze the image from global-area to local-area progressively. Then, we utilize the variance of the energy of wavelet coefficients within each image block, to decide the priority of inpainting blocks. Finally, we extract the multi-resolution features of each block. We take account of the correlation among horizontal, vertical and diagonal directions, to determine the inpainting strategy for filling image pixels and approximate a high-quality image inpainting to human vision. In our experiments, the performance of the proposed method is superior to the existing methods.

We show that distributed source coding of multi-view images in camera sensor networks (CSNs) using adaptive modules can come close to the Slepian-Wolf bound. In a systematic scenario with limited node abilities, work by Slepian and Wolf suggest that it is possible to encode statistically dependent signals in a distributed manner to the same rate as with a system where the signals are jointly encoded. We considered three nodes (PN, CN and CNs), which are statistically depended. Different distributed architecture solutions are proposed based on a parent node and child node framework. A PN sends the whole image whereas a CNs/CN only partially, using an adaptive coding based on adaptive module-operation at a rate close to theoretical bound - H(CNs|PN)/H(CN|PN,CNs). CNs sends sub-sampled image and encodes the rest of image, however CN encodes all image. In other words, the proposed scheme allows independent encoding and jointly decoding of views. Experimental results show performance close to the information-theoretic limit. Furthermore, good performance of the proposed architecture with adaptive scheme shows significant improvement over previous work.

A rate splitting algorithm is presented for a multiple video transmission system to transfer the aggregation (or statical multiplexing) of multiple video streams to multiple clients so that each client can receive the requested video stream with the reliable fidelity. Computer simulations for transmission of a set of 128 MPEG compressed video streams show that the proposed algorithm alleviates the variability of the aggregate video transmission comparing with a scheme to smooth individually each of videos using the traditional online smoothing algorithm. Besides, the proposed is 2 time faster than the traditional one.

Most of analytical models proposed so far for the IEEE 802.11 distributed coordination function (DCF) focus on saturation performance. In this paper, we develop an analytic model for unsaturation performance evaluation of the IEEE 802.11 DCF with and without slow contention window decrease (SCWD). The model explicitly takes into account the carrier sensing mechanism and an additional backoff interval after successful frame transmission, both of which can be ignored under saturation conditions. Expressions are derived for throughput and delay characteristics by means of the equilibrium point analysis. The accuracy of our model is validated through computer simulation. Numerical results based on the IEEE 802.11b with CCK show that the SCWD can stably achieve approximately 20% performance gain over the normal 802.11 DCF under unsaturation conditions as well as saturation ones.

This paper examines a coded Gaussian Minimum Shift Keying (GMSK) system which uses Reed-Solomon (RS) codes both in Additive White Gaussian Noise (AWGN) channels and Rayleigh fading channels. The performance of GMSK and RS code combinations is compared with the constraint that the transmitted signal bandwidth is constant. The coding gains were obtained using simulations and the best combination of GMSK and RS codes was found. The optimal code rates over AWGN and Rayleigh fading channels were also compared.

In this paper, we propose a single-user strategy for demodulating asynchronous direct-sequence code-division multiple access (DS/CDMA) signals for improving the performance of the adaptive receiver in fast fading channels. Since the adaptive receiver depends on the channel coefficient of all users, it cannot be implemented adaptively in fading channels due to severe tracking problem. A proposed adaptive receiver based on the modified minimum mean-squared-error (MMSE) criterion is used for solving this problem. By simulation, it is verified that our proposal is a promising method to solve the problem, and the results show that the proposed adaptive receiver has substantially larger capacity than the conventional adaptive receiver in fast fading channels.

A T user multiple access collision channel without feedback is considered where the channel inputs are called packets. The packets take values from non-binary input alphabet. It is supposed that at most M users are active, i.e., are communicating simultaneously (2 M T). We are looking for codes and protocol sequences of users of minimum length such that from the output of the channel it can be determined which users were active, what were their synchron positions, and what they sent.

In this paper, we propose and investigate space-time-frequency turbo coded OFDM transmissions through time-varying and frequency-selective fading channel. The proposed turbo code is a serial concatenated convolutional code which consists of space-frequency and time-frequency domain codes. The aim of the proposed turbo code is to obtain both diversity and coding gains over space-time-frequency domain. Using computer simulations and EXtrinsic Information Transfer (EXIT) charts, we investigate the optimum structure of inner and outer codes. Simulations demonstrate that the proposed system leads to significantly enhanced performance. Moreover, we analyze the computational complexity.

We introduce a differential space-time block code (DSTBC) integrated with trellis coded modulation with two transmit antennas. Our scheme enables transmission of DSTBC encoded symbols as trellis metric rather than concatenating an outer code. Unlike conventional DSTBC, different transmit symbol phase rotations are used for each transmit antenna in order to obtain more options for trellis branch. The set partitioning for proposed codes is derived as well. The decoder computes decision statistic using Viterbi Algorithm with different number of states undergoing Rayleigh fading channels. This approach can provide full diversity gain as well as coding gain simultaneously remaining full transmit rate, which cannot be obtained by conventional DSTBC.

This paper proposes a novel PN (Pseudo Noise) synchronization system using Cycle-and-Add property of M-sequence featuring fast acquisition in DS-CDMA (direct sequence-code division multiple access). Fast acquisition is carried out by generating a PN sequence in a simple multiplicative action of a received signal with its delayed one. This multiplicative action is similar to differentially coherent detection and realizes an anti-fading property. Easy implementation is materialized by the fact that the system is mostly composed of baseband devices. The principle, performance evaluation and the detection probability of synchronization for the proposed method are shown. Furthermore, detection probability of synchronization in a fast Rayleigh fading channel is shown for the performance evaluation.

Performance of the minimum mean square error (MMSE) detection is far below that of the maximum likelihood (ML) detection in a multiuser environment and decreases significantly as the number of co-channel users increases. In this paper, we propose a combined MMSE and ML multiuser detection scheme for space-time block coded (STBC) orthogonal frequency division multiplexing (STBC-OFDM) which has improved performance but with low complexity. In particular, we propose a reduced complexity ML post-detection (ML-PDP) scheme which can correct erroneously estimated bits from the outputs of MMSE multiuser detection. The proposed ML-PDP scheme performs sequential search to detect a predefined number of bits with higher probability of error and then uses ML detection to correct them. Upon controlling the number of corrected bits it is possible to balance the system performance with complexity associated with the ML-PDP. We show that significant improvement can be achieved at the cost of only small additional complexity compared with the MMSE multiuser detection.

This paper makes an examination of BER (bit error rate) performance in 22 MIMO (Multi-Input Multi-Output) systems using spatial multiplexing in a LOS (line-of-sight) environment by analysis using the eigenvalue and eigenvector of the channel matrix and simulation. It is shown that BER performance in a LOS environment is dependent on the phase relation of direct paths and the minimum squared absolute value of the eigenvalue, which are determined by the propagated distance. A technique for improving BER performance in a LOS environment is then considered based on these findings. A receive antenna selection (RAS) technique is presented which uses the minimum squared absolute value of the channel matrix eigenvalue. Proof is then given that BER performance is improved using this RAS technique, thus making clear the validity of this approach for obtaining optimum BER performance in a LOS environment.

The enormous capacity potential of multiple-input multiple-output (MIMO) is based on some unrealistic assumptions, such as the complete channel state information (CCSI) at the receiver and Gaussian distributed data. In this paper, in frequency-flat Rayleigh fading environment, we investigate the ergodic capacity of MIMO systems with M-ary phase-shift keying (MPSK) modulation and superimposed pilots for channel estimation. With linear minimum mean square error (LMMSE) channel estimation, the optimal pilots design is presented. For the mathematical tractability, we also derive an easy-computing closed-form lower bound of the channel capacity. Furthermore, the optimal power allocation between the data and pilots is investigated by numerical optimization. It is shown that more power should be devoted to the data in low SNR environments and to the pilots in high SNR environments.

In this manuscript, a layered macro/micro diversity scheme is introduced at the receiver side of a MIMO STBC wireless control system under fading and shadowing environment. The combination of the outputs of micro diversity is based on soft-decision values, while the macro diversity branches are combined based on hard decision values. As a measure of the reliability of the system, the outage probability of frame-error rate is employed. The performance of the proposed system is analytically and numerically evaluated and the impact of the macro diversity in the outage probability is clarified.

In this study, we present a way to choose route selection metric while discovering a new route in ad hoc mobile networks. We have used link expiration time and busy rate to calculate the route cost. The route cost is compared to a threshold value to decide whether the traffic of the route is high or low. If it is high then the system chooses busy rate as a route selection metric to avoid traffic congestion and if it is low the link expiration time is used to select the longlasting route. We have examined the characteristics of the routing protocol by computer simulation and found that it over performs the conventional protocols.

The letter presents an analysis of bit error probability for trellis coded 8-ary phase shift keying moduation with 2-state soft decision Viterbi decoding. It is shown that exact numerical error performance can be obtained for low singal-to-noise power ratio where bounds are useless.