Residual vector quantization using a multilayer competitive neural network
This paper presents a new technique for designing a jointly optimized residual vector quantizer (RVQ). In conventional stage-by-stage design procedure, each stage codebook is optimized for that particular stage distortion and does not consider the ...
Neural network techniques for adaptive multiuser demodulation
Adaptive methods for performing multiuser demodulation in a direct-sequence spread-spectrum multiple-access (DS/SSMA) communication environment are investigated. In this scenario, the noise is characterized as being the sum of the interfering users' ...
Omega network-based ATM switch with neural network-controlled bypass queueing and multiplexing
Multistage interconnection networks (MINs) have long been studied for use in switching networks. Since they have a unique path between source and destination and the intermediate nodes of the paths are shared, internal blocking can cause very poor ...
Neural scheduling algorithms for time-multiplex switches
In an N×N time-multiplex switch, transmission conflict arises when two or more input adaptors transmit packets to the same output adaptor simultaneously. To resolve transmission conflict, we propose two neural-based scheduling algorithms which use ...
Fuzzy neural control of voice cells in ATM networks
This paper presents the design of a fuzzy controller for managing cells generated by voice sources in asynchronous transfer mode (ATM) networks. Typical voice cells, characterized by a high degree of burstiness, complicate any attempt to use classical ...
Fuzzy rule-based signal processing and its application to image restoration
A novel signal processing technique based on fuzzy rules is proposed for estimating nonstationary signals, such as image signals, contaminated with additive random noises. In this filter, fuzzy rules concerning the relationship between signal ...
Quantizer neuron model and neuroprocessor-named quantizer neuron chip
A quantizer neuron model and a hardware implementation of the model is described. A quantizer neuron model and a multifunctional layered network (MFLN) with quantizer neurons is proposed and applied to a character recognition system. Each layer of MFLN ...
Adaptive interference suppression for CDMA overlay systems
It has been proposed that CDMA systems can be assigned to spectral bands which are presently occupied by narrowband users to further increase spectral capacity. Such CDMA overlay systems could provide new options for efficient utilization of the ...
Convergence properties of an adaptive lattice filter exploiting nonlinear dynamics of a biochemical reaction system
An adaptive lattice filter (ALF) which computes the PARCOR coefficients through a cyclic enzyme system has recently been developed by the author. Using nonlinear dynamics of the cyclic enzyme system, the ALF becomes robust against impulsive noise, and ...
A new IIR adaptive echo canceler: GIVE
A novel IIR adaptive gradient instrumental variable echo canceler (GIVE) is presented. Its features include adaptive controllability during double-talk periods in acoustic conference systems; guarantee of global convergence; low computational cost (the ...
Least mean p-power error criterion for adaptive FIR filter
An adaptive FIR filter based on the least mean p-power error (MPE) criterion is investigated. First, some useful properties of MPE function are studied. Three main results are as follows: 1) MPE function is a convex function of filter coefficients; so ...
A subband adaptive filter allowing maximally decimation
Conventional subband adaptive filters (ADF) using filter banks have shown degradation in performance because of the nonideal nature of filter banks. For this problem, the authors propose an alias free subband structure for adaptive filtering using ...
Intelligent control of signal processing algorithms in communications
In future telecommunications networks, an important role will be played by “intelligent control” techniques aimed at selecting and tuning signal processing (SP) algorithms. The authors first define the main problems of automatic control of ...
Knowledge model based approach in recognition of on-line Chinese characters
A knowledge model-based OCR system is presented for the recognition of on-line connected stroke Chinese characters. In the approach, segment attributes are first extracted to characterize the segment sequence of an unknown character. Next, radical ...
Linear prediction of subband signals
The performance of linear prediction of fullband and subband signals is described in terms of the respective prediction gain. The subband prediction gain is characterized in terms of the fullband signal power spectral density and the frequency response ...
A constrained joint source/channel coder design
The design of joint source/channel coders in situations where there is residual redundancy at the output of the source coder is examined. It has previously been shown that this residual redundancy can be used to provide error protection without a ...
Vector quantization using tree-structured self-organizing feature maps
In this paper, we propose a binary-tree structure neural network model suitable for structured clustering. During and after training, the centroids of the clusters in this model always form a binary tree in the input pattern space. This model is used to ...
Markov monitoring with unknown states
Pattern recognition methods and hidden Markov models can be effective tools for online health monitoring of communications systems. Previous work has assumed that the states in the system model are exhaustive. This can be a significant drawback in real-...
