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Study and Design of Differential Microphone Arrays

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Jacob Benesty, Jingdong Chen, "Study and Design of Differential Microphone Arrays"
English | 2013 | ISBN-10: 364233752X, 3642427561 | 180 pages | PDF | 6 MB

Study and Design of Differential Microphone Arrays
Microphone arrays have attracted a lot of interest over the last few decades since they have the potential to solve many important problems such as noise reduction/speech enhancement, source separation, dereverberation, spatial sound recording, and source localization/tracking, to name a few. However, the design and implementation of microphone arrays with beamforming algorithms is not a trivial task when it comes to processing broadband signals such as speech. Indeed, in most sensor arrangements, the beamformer output tends to have a frequency-dependent response. One exception, perhaps, is the family of differential microphone arrays (DMAs) who have the promise to form frequency-independent responses. Moreover, they have the potential to attain high directional gains with small and compact apertures. As a result, this type of microphone arrays has drawn much research and development attention recently. This book is intended to provide a systematic study of DMAs from a signal processing perspective. The primary objective is to develop a rigorous but yet simple theory

for the design, implementation, and performance analysis of DMAs. The theory includes some signal processing techniques for the design of commonly used first-order, second-order, third-order, and also the general Nth-order DMAs. For each order, particular examples are given on how to form standard directional patterns such as the dipole, cardioid, supercardioid, hypercardioid, subcardioid, and quadrupole. The study demonstrates the performance of the different order DMAs in terms of beampattern, directivity factor, white noise gain, and gain for point sources. The inherent relationship between differential processing and adaptive beamforming is discussed, which provides a better understanding of DMAs and why they can achieve high directional gain. Finally, we show how to design DMAs that can be robust against white noise amplification.
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“Trends in Neural Computation” ed. by Ke Chen, Lipo Wang

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"Trends in Neural Computation" ed. by Ke Chen, Lipo Wang
Studies in Computational Intelligence, Volume 35
S?ring?r | 2007 | ISBN: 3540361219 9783540361213 | 510 pages | PDF | 16 MB
This book reflects the progresses made in different areas of neural computation, including theoretical neural computation, biologically plausible neural modeling, computational cognitive science, artificial neural networks architectures and learning algorithms and their applications in real-world problems.

“Trends in Neural Computation” ed. by Ke Chen, Lipo Wang
Tte book includes twenty chapters either contributed from leading experts or formed by extending well selected papers presented in the 2005 International Conference on Natural Computation.

Contents
Preface
1 Hyperbolic Function Networks for Pattern Classification
2 Variable Selection for the Linear Support Vector Machine
3 Selecting Data for Fast Support Vector Machines Training
4 Universal Approach to Study Delayed Dynamical Systems
5 A Hippocampus-Neocortex Model for Chaotic Association
6 Latent Attractors: A General Paradigm for Context-Dependent Neural Computation
7 Learning Mechanisms in Networks of Spiking Neurons
8 GTSOM: Game Theoretic Self-organizing Maps
9 How to Generate Different Neural Networks
10 A Gradient-Based Forward Greedy Algorithm for Space Gaussian Process Regression
11 An Evolved Recurrent Neural Network and Its Application
12 A Min-Max Modular Network with Gaussian-Zero-Crossing Function
13 Combining Competitive Learning Networks of Various Representations for Sequential Data Clustering
14 Modular Neural Networks and Their Applications in Biometrics
15 Performance Analysis of Dynamic Cell Structures
16 Short Term Electric Load Forecasting: A Tutorial
17 Performance Improvement for Formation-Keeping Control Using a Neural Network HJI Approach
18 A Robust Blind Neural Equalizer Based on Higher-Order Cumulants
19 The Artificial Neural Network Applied to Servo Control System
20 Robot Localization Using Vision
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Handbook of Structural Engineering

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Handbook of Structural Engineering By W.F. Chen
1997 | 1600 Pages | ISBN: 0849326745 | PDF | 16 MB

Handbook of Structural Engineering
Covering the broad spectrum of modern structural engineering topics, the is a complete, single-volume reference. It includes the theoretical, practical, and computing aspects of the field, providing practicing engineers, consultants, students, and other interested individuals with a reliable, easy-to-use source of information.
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Principles and Techniques in Combinatorics

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Principles and Techniques in Combinatorics by Chen Chuan-Chong, Koh Khee-Meng
English | 1992 | ISBN: 9810211392 | 312 pages | PDF | 27 MB

Principles and Techniques in Combinatorics
A textbook suitable for undergraduate courses. The materials are presented very explicitly so that students will find it very easy to read. A wide range of examples, about 500 combinatorial problems taken from various mathematical competitions and exercises are also included.
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Granular Computing and Intelligent Systems: Design with Information Granules of Higher Order and Higher Type

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Witold Pedrycz, Shyi-Ming Chen, "Granular Computing and Intelligent Systems: Design with Information Granules of Higher Order and Higher Type
S inger | 2011 | ISBN: 3642198198 | 316 pages | PDF | 3 MB

Granular Computing and Intelligent Systems: Design with Information Granules of Higher Order and Higher Type
Information granules are fundamental conceptual entities facilitating perception of complex phenomena and contributing to the enhancement of human centricity in intelligent systems. The formal frameworks of information granules and information granulation comprise fuzzy sets, interval analysis, probability, rough sets, and shadowed sets, to name only a few representatives. Among current developments of Granular Computing, interesting options concern information granules of higher order and of higher type. The higher order information granularity is concerned with an effective formation of information granules over the space being originally constructed by information granules of lower order. This construct is directly associated with the concept of hierarchy of systems composed of successive processing layers characterized by the increasing levels of abstraction.
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Granular Computing and Intelligent Systems: Design with Information Granules of Higher Order and Higher Type

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Witold Pedrycz, Shyi-Ming Chen, "Granular Computing and Intelligent Systems: Design with Information Granules of Higher Order and Higher Type
S inger | 2011 | ISBN: 3642198198 | 316 pages | PDF | 3 MB

Granular Computing and Intelligent Systems: Design with Information Granules of Higher Order and Higher Type
Information granules are fundamental conceptual entities facilitating perception of complex phenomena and contributing to the enhancement of human centricity in intelligent systems. The formal frameworks of information granules and information granulation comprise fuzzy sets, interval analysis, probability, rough sets, and shadowed sets, to name only a few representatives. Among current developments of Granular Computing, interesting options concern information granules of higher order and of higher type. The higher order information granularity is concerned with an effective formation of information granules over the space being originally constructed by information granules of lower order. This construct is directly associated with the concept of hierarchy of systems composed of successive processing layers characterized by the increasing levels of abstraction.
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An Introduction to Stein’s Method

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A. D. Barbour, Louis H. Y. Chen, "An Introduction to Stein's Method"
2005 | ISBN-10: 981256280X, 8175961368 | 240 pages | PDF | 8 MB

An Introduction to Stein’s Method
A common theme in probability theory is the approximation of complicated probability distributions by simpler ones, the central limit theorem being a classical example. Stein's method is a tool which makes this possible in a wide variety of situations. Traditional approaches, for example using Fourier analysis, become awkward to carry through in situations in which dependence plays an important part, whereas Stein's method can often still be applied to great effect. In addition, the method delivers estimates for the error in the approximation, and not just a proof of convergence. Nor is there in principle any restriction on the distribution to be approximated; it can equally well be normal, or Poisson, or that of the whole path of a random process, though the techniques have so far been worked out in much more detail for the classical approximation theorems. This volume of lecture notes provides a detailed introduction to the theory and application of Stein's method, in a form suitable for graduate students who want to acquaint themselves with the method. It includes chapters treating normal, Poisson and compound Poisson approximation, approximation by Poisson processes, and approximation by an arbitrary distribution, written by experts in the different fields. The lectures take the reader from the very basics of Stein's method to the limits of current knowledge.
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ZK Ajax without the Javascript Framework by Henri Chen and Robbie Cheng

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ZK Ajax without the javascript Framework by Henri Chen and Robbie Cheng
Ap–ss | ISBN: 1590599012 | PDF | 125 pages | 7.5 MB


Book Description

ZK is the most popular open source SourceForge Ajax web framework that enables rich user interface for web applications with no javascript and little programming. This firstPress book will cover the following:

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