Digital Signal Processing

Key issues related to the modeling of ultra-high speed transmission are discussed in this paper. These topics include components modeling, link modeling and BER estimation. Different solutions for the transport of 100 Gb/s over a single wavelength including technologies such as coherent detection, polarization multiplexing, optical OFDM, and digital signal processing are reviewed and compared with means of numerical simulations.

The papers published in these proceedings are presented in the Third International Seminar on Maintenance, Condition Monitoring and Diagnostics, to be arranged in Oulu, Finland, in 29th – 30th September, 2010.

Arranged by the University of Oulu and POHTO – The Institute for Management and Technological Training, the present seminar is supported by a variety of Finnish industrial enterprises.

ISBN 978-951-98113-5-2

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Purpose-The purpose of this paper is to find a real-time parking location for a four-wheeler. Design/methodology/approach-Real-time parking availability using specific infrastructure requires a high cost of installation and maintenance cost, which is not affordable to all urban cities. The authors present statistical block matching algorithm (SBMA) for real-time parking management in small-town cities such as Bhavnagar using an in-built surveillance CCTV system, which is not installed for parking application. In particular, data from a camera situated in a mall was used to detect the parking status of some specific parking places using a region of interest (ROI). The method proposed computes the mean value of the pixels inside the ROI using blocks of different sizes (8 Â 10 and 20 Â 35), and the values were compared among different frames. When the difference between frames is more significant than a threshold, the process generates "no parking space for that place." Otherwise, the method yields "parking place available." Then, this information is used to print a bounding box on the parking places with the color green/red to show the availability of the parking place. Findings-The real-time feedback loop (car parking positions) helps the presented model and dynamically refines the parking strategy and parking position to the users. A whole-day experiment/validation is shown in this paper, where the evaluation of the method is performed using pattern recognition metrics for classification: precision, recall and F1 score. Originality/value-The authors found real-time parking availability for Himalaya Mall situated in Bhavnagar, Gujarat, for 18th June 2018 video using the SBMA method with accountable computational time for finding parking slots. The limitations of the presented method with future implementation are discussed at the end of this paper.

This paper presents a study for the orientation effectiveness on the detected areas for many sampled objects when many type of the edges detection are applied. The Canny, Laplace, Prewitt and Sobel are applied for three objects (pencils' sharpeners with different colors). The MBR (Minimal Bounding Rectangular) are used to calculate the area in pixels, centroid and the orientation. The MR (Misclassification Ratio) is used to find the different between the edges detection techniques. The Canny edges detection technique gives the best result for the three used object using all orientations.

We present the prototype of a hybrid instrument, which uses two contact microphones to sonify the gestures of a player on a generic surface, while a gesture localization algorithm controls the pitch of the sonified output depending on the position of the gestures. To achieve the gesture localization we use a novel approach combining attack parametrization and template matching across the two microphone channels. With this method we can correctly localize 80 ± 9 % of the percussive gestures. The user can assign determined pitches to specific positions and change the pitch palette in real time. The tactile feedback characteristic of every surface opens a set of new playing strategies and possibilities specific to any chosen object. The advantages of such a system are the affordable production, flexibility of concert location, object-specific musical instruments, portability, and easy setup.

Nonlinearities in optical fibers deteriorate system performances and become a major performancelimiting issue. This article aims to investigate the compensation of nonlinear distortions in optical communication systems based on different wavelength propagations over few-mode fiber (FMF). The study adopted Space Division Multiplexing (SDM) based on decision feedback equalizer (DFE). Various transmission wavelength of the FMF system is applied to mitigate the attenuation effect on the system. In this paper, different wavelengths (780, 850 and 1550 nm) are used in SDM. Extensive simulation is performed to assess the attenuation and Bit Error Rate (BER) in each case. The results show that the wavelength of 1550 nm produces higher power and less attenuation in the transmission. Furthermore, this wavelength produces the best distance with less BER compared to 780 nm and 850 nm wavelengths. Moreover, the validations show improvement in BER and eye diagram.

In this paper is simulated the time-domain unit sample response of sine function and frequency-domain response of sine function. Digital filter plays an important role in today's world of communication and computation. Without digital filter we cannot think about proper communication because noise occurs in channel. For removing noise or cancellation of noise we use various type of digital filter. In signal processing, there are mainly two types of filters exist .they are the Finite Impulse Response (FIR) filter and Infinite Impulse Response (IIR) filter. Finite Impulse Response (FIR) filter can be designed form Infinite Impulse Response (IIR) filter by various techniques. The widely used technique is the window technique. This paper low-pass FIR filter is implemented using an efficient adjustable window function based on Hamming window and Blackman window function. The output of the FIR design by Blackman window and the Blackman window are shown in this paper by simulating the code in Matlab. The Matlab program returns with a satisfactory result with proper magnitude plotting.

The paper analyses the possibility to recover different biomedical signals if limited number of samples is available. Having in mind that monitoring of health condition is done by measuring and observing key parameters such as heart activity through electrocardiogram or anatomy and body processes through magnetic resonance imaging, it is important to keep the quality of the reconstructed signal as better as possible. To recover the signal from limited set of available coefficients, the Compressive Sensing approach and optimization algorithms are used. The theory is verified by the experimental results.

The reliable condition monitoring of machines and the early detection of faults play an important role in condition-based maintenance. Information on the condition of machines is needed in different forms but finally it has to be in as simple form as possible so that it can be utilised in the decision-making by the maintenance and management personnel. In the field of machine condition monitoring, there is a wide range of signal processing methods, which are used in feature extraction and fault diagnosis. Differentiation and integration are very common and important operations in vibration signal processing. The order of derivative is typically an integer number but it can also be any fractional number. Especially in the challenging fault and process cases, signals whose order of derivative is a real or complex number could be clearly more sensitive in fault detection than the commonly used signals: displacement, velocity and acceleration. In this paper, the application of complex o...

This paper presents the design, sensing principles and in vitro evaluation of a novel instrumented sock intended for prediction and prevention of acute decompensated heart failure. The sock contains a drift-free ankle size sensor and a leg tissue elasticity sensor. Both sensors are inexpensive and developed using innovative new sensing ideas. Preliminary tests with the sensor prototypes show promising results: The ankle size sensor is capable of measuring 1 mm changes in ankle diameter and the tissue elasticity sensor can detect 0.15 MPa differences in elasticity. A low-profile instrumented sock prototype with these two sensors has been successfully fabricated and will be evaluated in the future in an IRB-approved human study.

his paper is concerned with a computational solution for normal optical flow estimation using space-variant image sampling. The article describes one solution for the problem based on log-Tpol ar images, including the algorithm implementation on digital signal processing hardware. The log-polar structure achieves high data compressing rates by maintaining a high resolution area-the fovea-and a space-variant resolution-the retinal periphery. This sampling scheme enables the implementation of selective processing, characteristic of attentive vision. The solution was developed to be used with an active vision system to pursue moving objects, assuming that the cameras could also move. Some properties of the log-polar structure are also described and the main results of the implementation are presented.

We present an introduction to some aspects of digital signal processing and time series analysis which are not always covered in classical textbooks. One of the objectives is to illustrate how mathematics and engineering can be combined in a fruitful interplay, resulting in many new techniques and methods in many different fields. We shall illustrate how the prediction problem is related to linear algebra, orthogonal polynomials, classical interpolation problems, inverse scattering theory, Toeplitz operators, network theory etc.

Speech compression is one area of digital signal processing that focusing on reducing the bit rate of the speech signal for transmission or storage without significant loss of quality. This paper presents a new design feature for speech Compression using Wavelet Packet Transform and Linear prediction Coding. The proposed algorithm uses best tree decomposition of wavelet packets, which develop features afterward compressed signal is compressed by Linear prediction Coding. The 4 points encoded vector is a full of information just like the original best tree’s structure. The implied scoring system makes BTE suitable for compression problems and we reach at 12 compression ratio. The performance of speech signal is measure on the basis of signal to noise ratio (SNR), mean square error (MSE) and peak signal to noise ratio (PSNR).

Analysis of heart rate variability (HRV) is a valuable, non-invasive method for quantifying autonomic cardiac control in humans. Frequency-domain analysis of HRV involving myocardial ischaemic episodes should take into account its non-stationary behaviour. The wavelet transform is an alternative tool for the analysis of non-stationary signals. Fourteen patients have been analysed, ranging from 40 to 64 years old and selected from the European Electrocardiographic ST-T Database (ESDB).

A system has been developed for digitally detecting superconducting magnet quenches in real time. This system has been fully tested and is completely integrated into a Vertical Magnet Test Facility (VMTF) at FNAL. The digital technique used for this system relies on the application of digital signal processing (DSP) algorithms running on a native Motorola PowerPC VME processor. The performance of this digital system has been shown to be superior to the analog technology typically used for quench detection; i.e., it detects resistive voltages reliably at low thresholds with minimum delay and is a more flexible system

During the last few years, spoken language technologies have known a big improvement thanks to Deep Learning. However Deep Learning-based algorithms require amounts of data that are often difficult and costly to gather. Particularly, modeling the variability in speech of different speakers, different styles or different emotions with few data remains challenging. In this paper, we investigate how to leverage fine-tuning on a pre-trained Deep Learning-based TTS model to synthesize speech with a small dataset of another speaker. Then we investigate the possibility to adapt this model to have emotional TTS by fine-tuning the neutral TTS model with a small emotional dataset.

The Clavinet is an electromechanical musical instrument produced in the mid-twentieth century. As is the case for other vintage instruments, it is subject to aging and requires great effort to be maintained or restored. This paper reports analyses conducted on a Hohner Clavinet D6 and proposes a computational model to faithfully reproduce the Clavinet sound in real time, from tone generation to the emulation of the electronic components. The string excitation signal model is physically inspired and represents a cheap solution in terms of both computational resources and especially memory requirements (compared, e.g., to sample playback systems). Pickups and amplifier models have been implemented which enhance the natural character of the sound with respect to previous work. A model has been implemented on a real-time software platform, Pure Data, capable of a 10-voice polyphony with low latency on an embedded device. Finally, subjective listening tests conducted using the current model are compared to previous tests showing slightly improved results.

Knowing rainforest environments is rendered challenging by distance, vegetation intensity, and coverage; however, knowing the complexity and sustainability of these landscapes is important for ecologists and conservationists. The airborne light detection and ranging (LiDAR) system has made dramatic improvements to forest data collection and management especially on the forest inventory aspect. LiDAR can reliably calculate tree-level characteristics such as crown scale and tree height as well as derived measures such as breast height diameter (DBH). To do this, an exact tree extraction method is needed inside LiDAR data. Within LiDAR data, tree extraction often starts by locating the treetops via local maxima (LM). Wide-ranging efforts have been developed to extract individual trees from LiDAR data by starting to localize treetops through LM within LiDAR data. Throughout this research, a demonstration of a new tree extraction framework inside LiDAR Point Cloud by incorporating a new tree extraction method using the bounding-box coordinates provided by deep learning-based object detection. Tree extraction inside the LiDAR point cloud using the bounding-box coordinates was successful and feasible.

One of the main tasks in structural health monitoring process is to create reliable algorithms that are capable of translating the measured response into meaningful information reflecting the actual condition of the monitored structure. The authors have recently introduced a novel unsupervised vibration-based damage detection algorithm that utilizes self-organizing maps to quantify structural damage and assess the overall condition of structures. Previously, this algorithm had been tested using the experimental data of Phase II Experimental Benchmark Problem of Structural Health Monitoring, introduced by the IASC (International Association for Structural Control) and ASCE (American Society of Civil Engineers). In this paper, the ability of this algorithm to quantify structural damage is tested analytically using an experimentally validated finite element model of a laboratory structure constructed at Qatar University.

A new digital-signal-processing method for performing modulation tests on Bluetooth transmitters is presented and validated. No preliminary demodulation of the radio frequency transmitted signal is needed to gain the instantaneous frequency trace, on which standard measurement procedures have to be applied. The aforementioned task is, in fact, fulfilled through the application of the short-time Fourier transform (STFT), a typical time-frequency representation, to the acquired samples of the aforementioned signal. Moreover, no specific information concerning the operating conditions of the transmitter under test, such as carrier frequency and hopping sequence, is needed, thus facilitating measurement automation. The optimal tuning of STFT parameters, which are capable of providing the best reconstruction of the instantaneous frequency trajectory as well as the most accurate measurement outcomes, is established as the result of an exhaustive experimental activity.

The automatic identification of sleep stages in electroencephalography (EEG) time-series is a long desired goal for researchers concerned with the study of sleep disorders. This paper presents advances towards achieving this goal, with particular application to EEG time-series recorded from mice. Approaches in the literature apply supervised learning classifiers, however, these do not reach the performance levels required for use within a laboratory. In this paper, detection reliability is increased, most notably in the case of REM stage identification, by naturally decomposing the problem and applying a support vector machine (SVM) based classifier to each of the EEG channels. Their outputs are integrated within a multiple classifier system. Furthermore, there exists no general consensus on the ideal choice of parameter values in such systems. Therefore, an investigation into the effects upon the classification performance is presented by varying parameters such as: the epoch length; features size; number of training samples; and the method for calculating the power spectral density estimate. Finally, the results of these investigations are brought together to demonstrate the performance of the proposed classification algorithm in two cases: intra-animal classification and inter-animal classification. It is shown that, within a dataset of ten EEG recordings, and using less than one percent of an EEG as training data, a mean classification error of Awake 6.45%, NREM 5.82%, and REM 6.65% (with standard deviations less than 0.6%) is achieved in intra-animal analysis and, when using the equivalent of seven percent of one EEG as training data, Awake 10.19%, NREM 7.75%, and REM 17.43% is achieved in inter-animal analysis (with mean standard deviations of 6.42%, 2.89%, and 9.69% respectively). A software package implementing the proposed approach will be made available through Cybula Ltd.

To subdivide the axis k into 2 new axes p and q, we place k=p+qN/r with p=0,1, ... , N/r s-1, s=0,1, ... ,logrN-1 and q = 0,1,...., r -1. Therefore, X(k) is replaced using new indices p and q where x [n] is the input sequence, X[k] is the output sequence, N is the transform length, w: k = e-j(2tr/N)nk is called the twiddle factor in the butterfly structure, and j2=_1. Both x [n] and X [k] are complex valued number sequences.

The field of Text-to-Speech has experienced huge improvements last years benefiting from deep learning techniques. Producing realistic speech becomes possible now. As a consequence, the research on the control of the expressiveness, allowing to generate speech in different styles or manners, has attracted increasing attention lately. Systems able to control style have been developed and show impressive results. However the control parameters often consist of latent variables and remain complex to interpret. In this paper, we analyze and compare different latent spaces and obtain an interpretation of their influence on expressive speech. This will enable the possibility to build controllable speech synthesis systems with an understandable behaviour.

Hardware and software systems are growing everyday in scale and functionality. This increase in complexity increases the number of subtle errors. Moreover, some of these errors may cause catastrophic loss of money, time, or even in many cases human life. A major goal of ...

Subband all-pole modelling is a flexible, scalable, and powerful approach for parsimoniously modelling rational transfer functions. Its advantage lies in its ability to model frequency bands independently of one another, thereby resulting in lower model orders in each subband and an overall reduction in the required number of parameters. To alleviate discontinuities in the spectrum at subband boundaries, it is necessary to increase slightly the computational complexity of the problem by incorporating continuity constraints. Previous solutions for implementing these constraints have been formulated for mathematical tractability and convenience; however, they are approximate and introduce modelling artifacts. This paper outlines an exact solution to the constrained modelling problem by using Lagrangian multipliers. The modelling results improve on the approximate formulations previously published.

Adaptive polar work-function predistortion (WFP) reduces the spectral regrowth of radio frequency power amplifiers such as those used in the telecommunications industry. This paper describes adaptive polar WFP equations and a system implementation. The system description includes an adaptive digital signal processing (DSP) algorithm based on measurement of outof-band performance. It includes a discussion of the strengths and weaknesses of the DSP algorithm used and presents some current results with wide-band modulation signals.

This paper discusses the design and field programmable gate array (FPGA) implementation of a configurable 18-tap fractionallyspaced blind adaptive equalizer intellectual property (IP) core for quadrature amplitude modulation (QAM) signals. The design can be configured to implement the constant modulus algorithm (CMA), multimodulus algorithm (MMA), radius-adjusted modifiedmultimodulus algorithm (RMMA), and radius-adjusted multimodulus decision-directed algorithm (RMDA), while it can achieve channel equalization for square QAM signals up to 256-QAM. The input samples to the equalizer tapped delay line are sampled at twice the symbol rate, while the equalizer output and tap coefficients are updated at the symbol rate. This is exploited by the equalizer tap and update modules of the design, which utilize the same hardware to implement two consecutive equalizer taps per module. The IP core is implemented for the Altera Stratix II EP2S130F780C4 FPGA and targets cable demodulators. The implementation operates at a maximum symbol frequency of 8.055 MBaud, which is comparable to recent QAM equalizer designs for cable modems. independently by Godard [7] and Treichler et al. . The success of CMA is due in part to its robustness and ability to converge prior to phase recovery. The multimodulus algorithm (MMA) [9,10] introduced by Yang et al. improves upon the performance of CMA by obtaining low steady-state mean-squared error (MSE), while eliminating the need for phase recovery in steady-state operation . Another class of blind equalization algorithms is known as hybrid blind equalization algorithms, which combine or augment existing cost functions to obtain enhanced performance. Two recent hybrid blind algorithms are the radius-adjusted modified-multimodulus algorithm (RMMA) and the radiusadjusted multimodulus decision-directed algorithm (RMDA), which were introduced by Banovic et al. . These algorithms modify their respective cost functions based on the equalizer output radius to improve the steady-state MSE and convergence time.

This paper concerns dynamic neural networks for signal processing: architectural issues are considered but the paper focuses on learning algorithms that work on-line. Locally recurrent neural networks, namely MLP with IIR synapses and generalization of Local Feedback Multi-Layered Networks (LF MLN), are compared to more traditional neural networks, i.e. static MLP with input and/or output buffer (TDNN), FIR MLP and fully recurrent neural networks: simulations results are provided to compare locally recurrent neural networks with TDNN and FIR MLP. Moreover, we propose a new learning algorithm, based on the Back Propagation Through Time and called Causal Back Propagation Through Time (CBPTT), that is faster and more stable than the algorithm previously used for IIR MLP. The algorithm that we propose includes as particular cases the following algorithms: Wan's Temporal Back Propagation, Back Propagation for Sequences (BPS) and Back-Tsoi algorithm.

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour-based invariants in the presence of large illumination changes between training and test data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) we employ a more sophisticated photometric model of the camera and show how its parameters can be estimated, (ii) we derive several novel colour-based face invariants, and (iii) on a large database of video sequences we examine and evaluate the largest number of colour-based representations in the literature. Our results suggest that colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images.

Mixing multitrack music is an expert task where characteristics of the individual elements and their sum are manipulated in terms of balance, timbre and positioning, to resolve technical issues and to meet the creative vision of the artist or engineer. In this paper we conduct a mixing experiment where eight songs are each mixed by eight different engineers. We consider a range of features describing the dynamic, spatial and spectral characteristics of each track, and perform a multidimensional analysis of variance to assess whether the instrument, song and/or engineer is the determining factor that explains the resulting variance, trend, or consistency in mixing methodology. A number of assumed mixing rules from literature are discussed in the light of this data, and implications regarding the automation of various mixing processes are explored. Part of the data used in this work is published in a new online multitrack dataset through which public domain recordings, mixes, and mix ...

Prezentowany rozdział otwierał drugą część popularnonaukowej książki "Inżynieria Biomedyczna". Część ta miała tytuł "Diagnostyka elektroniczna: Jak z pomocą maszyny śledzić procesy życiowe". Prezentowany tu rozdział wskazywał na to, jakie (ogólnie) sygnały można pozyskiwać z organizmu człowieka i co przy ich pomocy można osiągnąć w zakresie wspomagania diagnostyki medycznej i monitorowania terapii.

This paper presents an exploratory study about the improvement and validation of a Web-based educational tool. The tool, designed with Shockwave and Macromedia Director, is used as a teaching methodology in an undergraduate course using modern microprocessors, architectures, and applications. An information system theory, called the Technological Acceptance Model (TAM), has been applied to detect both the use of the tool and the external variables that have a significant influence over it. The obtained results illustrate the strengths and weaknesses to be reinforced and have been taken into account to implement the final version of the tool. The proposed method may be extended to similar tools and experiments to fill the lack of scientific studies in the validation and acceptance of computer-based educational tools.

— An automatic verification of person's identity from its voice is a part of modern telecommunication services. In order to execute a verification task, a speech signal has to be transmitted to a remote server. So, a performance of the verification system can be influenced by various distortions that can occur when transmitting a speech signal through a communication channel. This paper studies an effect of the state of art wideband (WB) speech codecs on a performance of automatic speaker verification in the context of a channel/codec mismatch between enrollment and test utterances. The speaker verification system is developed on GMM-UBM method. The results show that EVS codec provides the best performance over all the investigated scenarios in this study. Moreover, deploying G.729.1 codec in a training process of the verification system provides the best equal error rate in the fully-codec mismatched scenario. Anyhow, differences between the equal error rates reported for all of the codecs involved in this scenario are mostly nonsignificant.

Stridor and snoring are common signs of upper airway obstruction. The nature and characteristics of the stridor and snoring depend upon the site of obstruction. Sophisticated analysis of these sounds may provide important information concerning the source of the sound helping to assess the patient more objectively. The preliminary results of computerized digital analysis of stridor and snoring sounds are presented in 5 children. Two main programs were applied to analyse the signal:

The problem of establishing a mutually held secret cryptographic key using a radio channel is addressed. The performance of a particular key distribution system is evaluated for a practical mobile radio communications system. The performance measure taken is probabilistic, and different from the Shannon measure of perfect secrecy. In particular, it is shown that by using a channel decoder, the probability of two users establishing a secret key is close to one, while the probability of an adversary generating the same key is close to zero. The number of possible keys is large enough that exhaustive search is impractical. r

Abstrak menggunakan font 9. Abstrak adalah ringkasan singkat dari isi manuskrip, tidak lebih dari 200 kata. Abstrak seharusnya menggambarkan singkat tentang permasalahan yang dibahas dalam paper, metode yang digunakan unutk menjawab permasalahan tersebut, hasil yang didapat dan kesimpulan. Dengan membaca Abstrak, bisa langsung diketahui pokok bahasan yang ditulis dalam paper. Abstrak biasanya ditulis dalam satu atau dua paragraf, meskipun terletak di awal paper, umumnya abstrak ini lebih mudah ditulis jika paper telah selesai semuanya.