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Place Coding In Analog Vlsi

RRP $546.99

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Neurobiology research suggests that information can be represented by the location of an activity spot in a population of cells (`place coding'), and that this information can be processed by means of networks of interconnections. Place Coding in Analog VLSI defines a representation convention of similar flavor intended for analog-integrated circuit design. It investigates its properties and suggests ways to build circuits on the basis of this coding scheme.
In this electronic version of place coding, numbers are represented by the state of an array of nodes called a map, and computation is carried out by a network of links. In the simplest case, a link is just a wire connecting a node of an input map to a node of an output map. In other cases, a link is an elementary circuit cell. Networks of links are somewhat reminiscent of look-up tables in that they hardwire an arbitrary function of one or several variables. Interestingly, these structures are also related to fuzzy rules, as well as some types of artificial neural networks. The place coding approach provides several substantial benefits over conventional analog design:

  • Networks of links can be synthesized by a simple procedure whatever the function to be computed.
  • Place coding is tolerant to perturbations and noise in current-mode implementations.
  • Tolerance to noise implies that the fundamental power dissipation limits of conventional analog circuits can be overcome by using place coding.

The place coding approach is illustrated by three integrated circuits computing non-linear functions of several variables. The simplest one is made up of 80 links and achieves submicrowatt power consumption in continuous operation. The most complex one incorporates about 1800 links for a power consumption of 6 milliwatts, and controls the operation of an active vision system with a moving field of view.
Place Coding in Analog VLSI is primarily intended for researchers and practicing engineers involved in analog and digital hardware design (especially bio-inspired circuits). The book is also a valuable reference for researchers and students in neurobiology, neuroscience, robotics, fuzzy logic and fuzzy control.


Joint Source-channel Decoding

RRP $293.99

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Treats joint source and channel decoding in an integrated way
Gives a clear description of the problems in the field together with the mathematical tools for their solution
Contains many detailed examples useful for practical applications of the theory to video broadcasting over mobile and wireless networks



Traditionally, cross-layer and joint source-channel coding were seen as incompatible with classically structured networks but recent advances in theory changed this situation. Joint source-channel decoding is now seen as a viable alternative to separate decoding of source and channel codes, if the protocol layers are taken into account. A joint source/protocol/channel approach is thus addressed in this book: all levels of the protocol stack are considered, showing how the information in each layer influences the others.


This book provides the tools to show how cross-layer and joint source-channel coding and decoding are now compatible with present-day mobile and wireless networks, with a particular application to the key area of video transmission to mobiles. Typical applications are broadcasting, or point-to-point delivery of multimedia contents, which are very timely in the context of the current development of mobile services such as audio (MPEG4 AAC) or video (H263, H264) transmission using recent wireless transmission standards (DVH-H, DVB-SH, WiMAX, LTE).


This cross-disciplinary book is ideal for graduate students, researchers, and more generally professionals working either in signal processing for communications or in networking applications, interested in reliable multimedia transmission. This book is also of interest to people involved in cross-layer optimization of mobile networks. Its content may provide them with other points of view on their optimization problem, enlarging the set of tools which they could use.

Pierre Duhamel is director of research at CNRS/ LSS and has previously held research positions at Thomson-CSF, CNET, and ENST, where he was head of the Signal and Image Processing Department. He has served as chairman of the DSP committee and associate Editor of the IEEE Transactions on Signal Processing and Signal Processing Letters, as well as acting as a co-chair at MMSP and ICASSP conferences. He was awarded the Grand Prix France Telecom by the French Science Academy in 2000. He is co-author of more than 80 papers in international journals, 250 conference proceedings, and 28 patents.


Michel Kieffer is an assistant professor in signal processing for communications at the Universite Paris-Sud and a researcher at the Laboratoire des Signaux et Systemes, Gif-sur-Yvette, France. His research interests are in joint source-channel coding and decoding techniques for the reliable transmission of multimedia contents. He serves as associate editor of Signal Processing (Elsevier). He is co-author of more than 90 contributions to journals, conference proceedings, and book chapters.
Treats joint source and channel decoding in an integrated way
Gives a clear description of the problems in the field together with the mathematical tools for their solution
Contains many detailed examples useful for practical applications of the theory to video broadcasting over mobile and wireless networks


Trellis Decoding Of Block Codes

RRP $546.99

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It is a great pleasure to be asked to write the Preface for this book on trellis decoding of error correcting block codes. The subject is extremely significant both theoretically and practically, and is very timely because of recent devel- opments in the microelectronic implementation and range of application of error-control coding systems based on block codes. The authors have been notably active in signal processing and coding research and development for several years, and therefore very well placed to contribute to the state of the art on the subject of trellis decoding. In particular, the book represents a unique approach to many practical aspects of the topic. As the authors point out, there are two main classes of error control codes: block codes and convolutinal codes. Block codes came first historically and have a well-developed mathematical structure. Convolutional codes come later, and have developed heuristically, though a more formal treatment has emerged via recent developments in the theory of symbolic dynamics. Max- imum likelihood (ML) decoding of powerful codes in both these classes is computationally complex in the general case; that is, ML decoding fails into the class of NP-hard computational problems. This arieses because the de- coding complexity is an exponential function of key parameters of the code.



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