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Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first mathematically rigorous account of the fundamental theory underlying these applications. The emphasis is on the asymptotics of quantization errors for absolutely continuous and special classes of singular probabilities (surface measures, self-similar measures) presenting some new results for the first time. Written for researchers and graduate students in probability theory the monograph is of potential interest to all people working in the disciplines mentioned above.
This book contains select contributions presented at the International Conference on Nonlinear Applied Analysis and Optimization (ICNAAO-2021), held at the Department of Mathematics Sciences, Indian Institute of Technology (BHU) Varanasi, India, from 21–23 December 2021. The book discusses topics in the areas of nonlinear analysis, fixed point theory, dynamical systems, optimization, fractals, applications to differential/integral equations, signal and image processing, and soft computing, and exposes the young talents with the newer dimensions in these areas with their practical approaches and to tackle the real-life problems in engineering, medical and social sciences. Scientists from the U.S.A., Austria, France, Mexico, Romania, and India have contributed their research. All the submissions are peer reviewed by experts in their fields.
This book provides the first comprehensive and easy-to-read discussion of joint source-channel encoding and decoding for source signals with continuous amplitudes. It is a state-of-the-art presentation of this exciting, thriving field of research, making pioneering contributions to the new concept of source-adaptive modulation.The book starts with the basic theory and the motivation for a joint realization of source and channel coding. Specialized chapters deal with practically relevant scenarios such as iterative source-channel decoding and its optimization for a given encoder, and also improved encoder designs by channel-adaptive quantization or source-adaptive modulation.Although Information Theory is not the main topic of the book ? in fact, the concept of joint source-channel coding is contradictory to the classical system design motivated by a questionable practical interpretation of the separation theorem ? this theory still provides the ultimate performance limits for any practical system, whether it uses joint source-channel coding or not. Therefore, the theoretical limits are presented in a self-contained appendix, which is a useful reference also for those not directly interested in the main topic of this book.
"Wireless communications is one of the most important modern technologies and is interwoven with all aspects of our daily lives. When we wake up, we check social media, email, and news on our smartphones. Before getting up, we adjust the room temperature through a Bluetooth-connected thermostat. After we leave the house and activate the Wi-Fi security cameras, we order a rideshare on a phone app that recognizes our location and are driven to a factory where manufacturing robots are connected and controlled via 5G. And that is only the start of the day.... It is thus no wonder that wireless infrastructure, user devices, and networks are among the largest and most critical industries in most countries. As the demands for wireless services constantly increase, so are the requirements for new products, and for engineers that can develop these products and bring them to market. Such engineers need a deep understanding of both the fundamentals that govern the behavior of wireless systems, the current standardized systems implementations, and more recent research developments that will influence the next generation of products. The goal of this book is to help students, researchers, and practicing engineers to acquire, refresh, or update this knowledge. It is designed to lead them from the fundamental principles and building blocks, such as digital modulation, fading, and reuse of spectrum, to more advanced technologies that underly modern wireless systems, such as multicarrier and multiantenna transmission, to a description of the standardized systems dominating 5G cellular, Wi-Fi, and short-range communications, to the cutting-edge research that will form the basis for beyond-5G systems. In brief, the book leads the reader from the fundamentals to beyond 5G"--
This volume contains the papers presented at ESA 2009: The 17th Annual - ropean Symposium on Algorithms, September 7–9, 2009. ESA has been held annually since 1993, and seeks to cover both theoretical and engineering aspects of algorithms. The authors were asked to classify their paper under one or more categories as described in Fig. 1. Since 2001, ESA has been the core of the larger ALGO conference, which typically includes several satellite conferences. ALGO 2009 was held at the IT University of Copenhagen, Denmark. The ?ve members of the ALGO 2009 - ganizing Committee were chaired by Thore Husfeldt. The ESA submission deadline was April 12, Easter Sunday. This was clearly an error and we o?er profuse apologies for this mistake. Albeit no excuse, the hard constraints we faced were (a) ICALP noti?cation, April 6, and (b) ESA in Copenhagen, September 7. Between these two endpoints we needed to design a schedule that allowed modifying ICALP rejections for resubmission (1 week), Program Committee deliberations (7 weeks), preparing ?nal versions (4 weeks), and, to prepare, publish, and transport the proceedings (9 weeks). ESA 2009had 272submissions ofwhich 14 werewithdrawn overtime. Of the remaining 222 submissions to Track A (Design and Analysis), 56 were accepted. Of the remaining 36 submissions to Track B (Engineering and Applications), 10 were accepted. This gives an acceptance rate of slightly under 25%.
This book contains the proceedings of the International Confer ence on Artificial Neural Networks which was held between September 13 and 16 in Amsterdam. It is the third in a series which started two years ago in Helsinki and which last year took place in Brighton. Thanks to the European Neural Network Society, ICANN has emerged as the leading conference on neural networks in Europe. Neural networks is a field of research which has enjoyed a rapid expansion and great popularity in both the academic and industrial research communities. The field is motivated by the commonly held belief that applications in the fields of artificial intelligence and robotics will benefit from a good understanding of the neural information processing properties that underlie human intelligence. Essential aspects of neural information processing are highly parallel execution of com putation, integration of memory and process, and robustness against fluctuations. It is believed that intelligent skills, such as perception, motion and cognition, can be easier realized in neuro-computers than in a conventional computing paradigm. This requires active research in neurobiology to extract com putational principles from experimental neurobiological find ings, in physics and mathematics to study the relation between architecture and function in neural networks, and in cognitive science to study higher brain functions, such as language and reasoning. Neural networks technology has already lead to practical methods that solve real problems in a wide area of industrial applications. The clusters on robotics and applications contain sessions on various sub-topics in these fields.
"This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
Herb Caen, a popular columnist for the San Francisco Chronicle, recently quoted a Voice of America press release as saying that it was reorganizing in order to "eliminate duplication and redundancy. " This quote both states a goal of data compression and illustrates its common need: the removal of duplication (or redundancy) can provide a more efficient representation of data and the quoted phrase is itself a candidate for such surgery. Not only can the number of words in the quote be reduced without losing informa tion, but the statement would actually be enhanced by such compression since it will no longer exemplify the wrong that the policy is supposed to correct. Here compression can streamline the phrase and minimize the em barassment while improving the English style. Compression in general is intended to provide efficient representations of data while preserving the essential information contained in the data. This book is devoted to the theory and practice of signal compression, i. e. , data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general purpose computer data). The emphasis is on the conversion of analog waveforms into efficient digital representations and on the compression of digital information into the fewest possible bits. Both operations should yield the highest possible reconstruction fidelity subject to constraints on the bit rate and implementation complexity.
Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the 1960s, it evolved into an automatic classification technique for generating prototypes of extensive datasets. In modern terms, it can be recognized as a seminal contribution to unsupervised learning through the k-means clustering algorithm in data science. In contrast, Functional Quantization, a more recent area of study dating back to the early 2000s, focuses on the quantization of continuous-time stochastic processes viewed as random vectors in Banach function spaces. This book distinguishes itself by delving into the quantization of random vectors with values in a Banach space—a unique feature of its content. Its main objectives are twofold: first, to offer a comprehensive and cohesive overview of the latest developments as well as several new results in optimal quantization theory, spanning both finite and infinite dimensions, building upon the advancements detailed in Graf and Luschgy's Lecture Notes volume. Secondly, it serves to demonstrate how optimal quantization can be employed as a space discretization method within probability theory and numerical probability, particularly in fields like quantitative finance. The main applications to numerical probability are the controlled approximation of regular and conditional expectations by quantization-based cubature formulas, with applications to time-space discretization of Markov processes, typically Brownian diffusions, by quantization trees. While primarily catering to mathematicians specializing in probability theory and numerical probability, this monograph also holds relevance for data scientists, electrical engineers involved in data transmission, and professionals in economics and logistics who are intrigued by optimal allocation problems.
And the downloadable software gives you the opportunity to see firsthand how various algorithms work, to choose and implement appropriate techniques in your own applications, and to build your own algorithms."--BOOK JACKET.