103 research outputs found

    One-pass adaptive universal vector quantization

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    The authors introduce a one-pass adaptive universal quantization technique for real, bounded alphabet, stationary sources. The algorithm is set on line without any prior knowledge of the statistics of the sources which it might encounter and asymptotically achieves ideal performance on all sources that it sees. The system consists of an encoder and a decoder. At increasing intervals, the encoder refines its codebook using knowledge about incoming data symbols. This codebook is then described to the decoder in the form of updates on the previous codebook. The accuracy to which the codebook is described increases as the number of symbols seen, and thus the accuracy to which the codebook is known, grows

    Universal multiresolution source codes

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    A multiresolution source code is a single code giving an embedded source description that can be read at a variety of rates and thereby yields reproductions at a variety of resolutions. The resolution of a source reproduction here refers to the accuracy with which it approximates the original source. Thus, a reproduction with low distortion is a “high-resolution” reproduction while a reproduction with high distortion is a “low-resolution” reproduction. This paper treats the generalization of universal lossy source coding from single-resolution source codes to multiresolution source codes. Results described in this work include new definitions for weakly minimax universal, strongly minimax universal, and weighted universal sequences of fixed- and variable-rate multiresolution source codes that extend the corresponding notions from lossless coding and (single-resolution) quantization to multiresolution quantizers. A variety of universal multiresolution source coding results follow, including necessary and sufficient conditions for the existence of universal multiresolution codes, rate of convergence bounds for universal multiresolution coding performance to the theoretical bound, and a new multiresolution approach to two-stage universal source coding

    Study and simulation of low rate video coding schemes

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    The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design

    Recent advances on recursive filtering and sliding mode design for networked nonlinear stochastic systems: A survey

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    Copyright © 2013 Jun Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Some recent advances on the recursive filtering and sliding mode design problems for nonlinear stochastic systems with network-induced phenomena are surveyed. The network-induced phenomena under consideration mainly include missing measurements, fading measurements, signal quantization, probabilistic sensor delays, sensor saturations, randomly occurring nonlinearities, and randomly occurring uncertainties. With respect to these network-induced phenomena, the developments on filtering and sliding mode design problems are systematically reviewed. In particular, concerning the network-induced phenomena, some recent results on the recursive filtering for time-varying nonlinear stochastic systems and sliding mode design for time-invariant nonlinear stochastic systems are given, respectively. Finally, conclusions are proposed and some potential future research works are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grant nos. 61134009, 61329301, 61333012, 61374127 and 11301118, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant no. GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

    Adaptive hierarchical vector quantization for image coding: new results

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    Adaptive hierarchical algorithms of vector quantization (VQ) for image coding are proposed. First, the basic codebook is generated adaptively using adaptive VQ, then the quadruplets of codes/indices in the so-called zigzag order are coded into higher level (second and third levels) codes by creating the second- and third-level index codebooks to reduce the redundancy presented in the codes. Partially matched quadruplets are also encoded in the second and third layers using index codebooks along with corresponding correction schemes. The third-layer encoding achieves a better compression ratio than a two-layer encoding scheme, which was shown to be optimal when partial encoding was not adopted. This three-layer coding scheme achieves better compression with no extra distortion and little extra computation. Experiments show encouraging results.published_or_final_versio

    Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems

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    We examine the problem of uplink cell-free access point (AP) placement in the context of optimal throughput. In this regard, we formulate two main placement problems, namely the sum rate and minimum rate maximization problems, and discuss the challenges associated with solving the underlying optimization problem with the help of some simple scenarios. As a practical solution to the AP placement problem, we suggest a vector quantization (VQ) approach. The suitability of the VQ approach to cell-free AP placement is investigated by examining three VQ-based solutions. First, the standard VQ approach, that is the Lloyd algorithm (using the squared error distortion function) is described. Second, the tree-structured VQ (TSVQ), which performs successive partitioning of the distribution space is applied. Third, a probability density function optimized VQ (PDFVQ) procedure is outlined, which enables efficient, low complexity, and scalable placement, and is aimed at a massive distributed multiple-input-multiple-output (MIMO) scenario. While the VQ-based solutions do not solve the cell-free AP placement problems explicitly, numerical experiments show that their sum and minimum rate performances are good enough, and offer a good starting point for gradient-based optimization methods. Among the VQ solutions, PDFVQ, with advantages over the other VQ methods, offers a good trade-off between sum and minimum rates.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

    Dynamic element matching techniques for data converters

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    Analog to digital converter (ADC) circuit component errors create nonuniform quantization code widths and create harmonic distortion in an ADC\u27s output. In this dissertation, two techniques for estimating an ADC\u27s output spectrum from the ADC\u27s transfer function are determined. These methods are compared to a symmetric power function and asymmetric power function approximations. Standard ADC performance metrics, such as SDR, SNDR, SNR, and SFDR, are also determined as a function of the ADC\u27s transfer function approximations. New dynamic element matching (DEM) flash ADCs are developed. An analysis of these DEM flash ADCs is developed and shows that these DEM algorithms improve an ADC\u27s performance. The analysis is also used to analyze several existing DEM ADC architectures; Digital to analog converter (DAC) circuit component errors create nonuniform quantization code widths and create harmonic distortion in a DAC\u27s output. In this dissertation, an exact relationship between a DAC\u27s integral nonlinearity (INL) and its output spectrum is determined. Using this relationship, standard DAC performance metrics, such as SDR, SNDR, SNR, and SFDR, are calculated from the DAC\u27s transfer function. Furthermore, an iterative method is developed which determines an arbitrary DAC\u27s transfer function from observed output magnitude spectra. An analysis of DEM techniques for DACs, including the determination of several suitable metrics by which DEM techniques can be compared, is derived. The performance of a given DEM technique is related to standard DAC performance metrics, such as SDR, SNDR, and SFDR. Conditions under which DEM techniques can guarantee zero average INL and render the distortion due to mismatched components as white noise are developed. Several DEM circuits proposed in the literature are shown to be equivalent and have hardware efficient implementations based on multistage interconnection networks. Example DEM circuit topologies and their hardware efficient VLSI implementations are also presented
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