Intelligent Methods in Signal Processing and Communications

by Docampo, D.; Figuerias-Vidal, A. R.; Perez-Gonzalez, F.

• ISBN13: 9780817639600
• ISBN10: 0817639608
• Format: Hardcover
• Copyright: 1997-04-01
• Publisher: Birkhauser

Summary

Modern Historiographyis the essential introduction to the history of historical writing. It explains the broad philosophical background to the different historians and historical schools of the modern era. In a unique overview of modern historiography, the book includes surveys on the Enlightenment and Counter Enlightenment; Romanticism; the voice of Science and the process of secularization within Western intellectual thought; the influence of, and broadening contact with, the New World; theAnnalesschool in France; and the effects of the repression and exile of the inter-war years and the Post-War 'moods.'Modern Historiographyprovides a clear and concise account of this modern period of historical writing.

Table of Contents

List of Contributors	xi	(4)
Preface	xv
1 Adaptive Antenna Arrays in Mobile Communications	1	(14)
L. J. Griffiths
1.1 Introduction	1	(2)
1.2 Adaptive Arrays in Base Station Antennas	3	(2)
1.3 Adaptive Array Details	5	(2)
1.4 LMS Adaptive Array Examples	7	(1)
1.5 Desired Signal Availability	8	(3)
1.6 Discussion and Observations	11	(2)
1.7 References	13	(2)
2 Demodulation in the Presence of Multiuser Interference: Progress and Misconceptions	15	(32)
S. Verdu
2.1 Introduction	15	(1)
2.2 Single-user Matched Filter	16	(3)
2.3 Optimum Multiuser Detection	19	(3)
2.4 Linear Multiuser Detection	22	(5)
2.5 Decision-based Multiuser Detection	27	(1)
2.6 Noncoherent Multiuser Detection	28	(1)
2.7 Multiuser Detection combined with Array Processing	28	(1)
2.8 Multiuser Detection with Error Control Coded Data	29	(3)
2.9 References	32	(15)
3 Intelligent Signal Detection	47	(16)
S. Haykin
3.1 Introduction	47	(1)
3.2 Three Basic Elements Of The Intelligent Detection System	48	(5)
3.3 Neural Network-Based Two-Channel Receiver	53	(1)
3.4 Rationale For The Modular Detection Strategy	54	(3)
3.5 Case Study	57	(1)
3.6 Summary And Discussion	58	(2)
3.7 References	60	(3)
4 Biometric Identification for Access Control	63	(36)
S. Lin
S. Y. Kung
4.1 Introduction	64	(2)
4.2 Feature Extraction for Biometric Identification	66	(4)
4.2.1 Geometric Features	67	(1)
4.2.2 Template Features	68	(2)
4.3 Pattern Classification for Biometric Identification	70	(4)
4.3.1 Statistical Pattern Recognition	70	(2)
4.3.2 Neural Networks	72	(2)
4.4 Probabilistic Decision-Based Neural Network	74	(6)
4.4.1 Discriminant Functions of PDBNN	74	(1)
4.4.2 Learning Rules for PDBNN	75	(3)
4.4.3 Extension of PDBNN to Multiple-Class Pattern Recognition	78	(2)
4.5 Biometric Identification by Human Faces	80	(7)
4.5.1 Face Detection	82	(2)
4.5.2 Eye Localization	84	(2)
4.5.3 Face Recognition	86	(1)
4.6 Biometric Identification by Palm Prints	87	(6)
4.6.1 Feature Extraction for Palm Print Recognition	87	(1)
4.6.2 Pattern Classification for Palm Print Recognition	88	(3)
4.6.3 Experimental Results	91	(2)
4.7 Concluding Remarks	93	(1)
4.8 References	94	(5)
5 Multidimensional Nonlinear Myopic Maps, Volterra Series, and Uniform Neural-Network Approximations	99	(30)
I. W. Sandberg
5.1 Introduction	99	(3)
5.2 Approximation of Myopic Maps	102	(9)
5.2.1 Preliminaries	102	(1)
5.2.2 Our Main Result	103	(4)
5.2.3 Comments	107	(2)
5.2.4 Finite Generalized Volterra-Series Approximations	109	(2)
5.3 Appendices	111	(15)
5.3.1 H.1. Preliminaries and the Approximation Result	122	(4)
5.4 References	126	(3)
6 Monotonicity: Theory and Implementation	129	(18)
J. Sill
Y. Abu-Mostafa
6.1 Introduction	129	(2)
6.2 Representation of hints	131	(3)
6.3 Monotonicity hints	134	(5)
6.4 Theory	139	(6)
6.4.1 Capacity results	140	(4)
6.4.2 Decision boundaries	144	(1)
6.5 Conclusion	145	(1)
6.6 References	146	(1)
7 Analysis and Synthesis Tools for Robust SP Rness	147	(26)
C. Mosquera
J.R. Hernandez
F. Perez-Gonzalez
7.1 Introduction	147	(6)
7.2 SPR Analysis of Uncertain Systems	153	(8)
7.2.1 The Polytopic Case	155	(2)
7.2.2 The l(p)-Ball Case	157	(2)
7.2.3 The Roots Space Case	159	(2)
7.3 Synthesis of LTI Filters for Robust SPR Problems	161	(6)
7.3.1 Algebraic Design for Two Plants	161	(3)
7.3.2 Algebraic Design for Three or More Plants	164	(1)
7.3.3 Approximate Design Methods	165	(2)
7.4 Experimental results	167	(1)
7.5 Conclusions	168	(1)
7.6 References	169	(4)
8 Boundary Methods for Distribution Analysis	173	(26)
J.L. Sancho et al.
8.1 Introduction	173	(3)
8.1.1 Building a Classifier System	175	(1)
8.2 Motivation	176	(1)
8.3 Boundary Methods as Feature-Set Evaluation	177	(5)
8.3.1 Results	179	(3)
8.3.2 Feature Set Evaluation using Boundary Methods: Summary	182	(1)
8.4 Boundary Methods as a Sample-Pruning (SP) Mechanism	182	(3)
8.4.1 Description of the simulations	184	(1)
8.4.2 Results	184	(1)
8.4.3 Sample Pruning using Boundary Methods: Summary	185	(1)
8.5 Boundary Methods as Fisher's Linear Discriminant (FLD)	185	(1)
8.6 Conclusions	186	(1)
8.7 Apendix: Proof of the Theorem Relating FLD and Boundary Methods	186	(5)
8.7.1 Assumptions and Definitions	186	(1)
8.7.2 Fisher's Linear Discriminant (FLD) Analysis	187	(1)
8.7.3 Unicity of the Tangent Point Equivalent to FLD	188	(1)
8.7.4 Elliptic Tangent Point with the Equal Magnitude and Opposite Sign of the Gradient	189	(2)
8.8 References	191	(8)
9 Constructive Function Approximation: Theory and Practice	199	(22)
D. Docampo
D. Hush
C.T. Abdallah
9.1 Introduction	199	(1)
9.2 Overview of Constructive Approximation	200	(1)
9.3 Constructive Solutions	201	(4)
9.3.1 Discussion	203	(2)
9.4 Limits and Bounds of the Approximation	205	(4)
9.4.1 Minimum Global Error	206	(1)
9.4.2 Fixing XXXn	207	(1)
9.4.3 Fixing the rate of convergence	208	(1)
9.5 The Sigmoidal Class of Approximators	209	(1)
9.6 Practical Considerations	210	(7)
9.6.1 Projection Pursuit Methods	212	(1)
9.6.2 Projection Pursuit with Neural Networks	213	(4)
9.7 Conclusions	217	(1)
9.8 Acknowledgments	217	(1)
9.9 References	217	(4)
10 Decision Trees Based on Neural Networks	221	(22)
J. Cid-Sueiro
J. Ghattas
A.R. Figueiras-Vidal
10.1 Introduction	221	(2)
10.2 Adaptive modular classifiers	223	(2)
10.2.1 The classification problem	223	(1)
10.2.2 Splitting the input space	223	(2)
10.2.3 Supervised and non-supervised learning	225	(1)
10.3 A survey on tree classification	225	(3)
10.3.1 Hypercubic cells	225	(2)
10.3.2 Thresholding attributes	227	(1)
10.3.3 Linear Combinations of the Attributes	227	(1)
10.4 Neural Decision Trees	228	(1)
10.5 Hierarchical mixtures of experts	229	(6)
10.5.1 Soft decision classifiers	229	(1)
10.5.2 Training HME classifiers	230	(1)
10.5.3 Applying the EM algorithm	231	(4)
10.6 Lighting the hidden variables	235	(1)
10.7 Conclusions	235	(4)
10.8 References	239	(4)
11 Applications of Chaos in Communications	243	(20)
M. P. Kennedy
11.1 Introduction	243	(1)
11.2 Deterministic dynamical systems and chaos	243	(1)
11.3 Chua's oscillator: a paradigm for chaos	244	(1)
11.4 Periodicity, quasiperiodicity, and chaos	245	(2)
11.5 Applications of chaos in communications	247	(1)
11.6 Digital communication	247	(2)
11.7 Spreading	249	(2)
11.7.1 Pseudorandom spreading sequences	250	(1)
11.7.2 Chaotic spreading signals	251	(1)
11.8 Chaotic synchronization: state of the art	251	(1)
11.8.1 Drive-response synchronization	251	(1)
11.8.2 Inverse systems	252	(1)
11.8.3 Error-feedback synchronization	252	(1)
11.8.4 Performance evaluation	252	(1)
11.9 Chaotic modulation: state of the art	252	(3)
11.9.1 Chaotic masking	252	(1)
11.9.2 Inverse systems	253	(1)
11.9.3 Predictive Poincare Control (PPC) modulation	253	(1)
11.9.4 Chaos Shift Keying (CSK)	254	(1)
11.9.5 Differential Chaos Shift Keying (DCSK)	255	(1)
11.10 Chaotic demodulation: state of the art	255	(1)
11.10.1 Coherent demodulation by chaos synchronization	255	(1)
11.10.2 Noncoherent demodulation	256	(1)
11.11 Additional considerations	256	(1)
11.11.1 Security issues	256	(1)
11.11.2 Multiple access	256	(1)
11.12 Engineering challenges	257	(1)
11.13 References	257	(6)
12 Design of Near PR Non-Uniform Filter Banks	263	(18)
F. Argenti
B. Brogelli
E. Del Re
12.1 Introduction	263	(3)
12.2 The MPEG audio coder	266	(2)
12.3 Non-uniform filter banks with rational sampling factors	268	(6)
12.3.1 Aliasing cancellation in non-uniform filter banks	268	(4)
12.3.2 Use of cosine-modulated filter banks	272	(2)
12.4 Examples of non-uniform filter banks design	274	(2)
12.5 Conclusions	276	(1)
12.6 References	276	(5)
13 Source Coding of Stereo Pairs	281	(20)
H. Aydinoglu
M. H. Hayes
13.1 Introduction	281	(1)
13.2 Stereo Image Coding	282	(5)
13.2.1 Theory of Stereo Image Coding	283	(2)
13.2.2 Historical Perspective	285	(2)
13.3 The Subspace Projection Technique	287	(6)
13.4 Experimental Results	293	(1)
13.5 Conclusion	294	(4)
13.6 References	298	(3)
14 Design Methodology for VLSI Implementation of Image and Video Coding Algorithms - A Case Study	301
J. Bracamonte
M. Ansorge
F. Pellandini
14.1 Introduction	301	(1)
14.2 JPEG Baseline Algorithm	302	(3)
14.3 High Level Modeling	305	(3)
14.4 VLSI Architectures	308	(5)
14.4.1 FDCT	309	(3)
14.4.2 Quantizer	312	(1)
14.4.3 Entropy coder	312	(1)
14.5 Bit-true Level Modeling	313	(2)
14.6 Layout Design	315	(1)
14.7 Results	316	(1)
14.7.1 Extensions for Video Coding	316	(1)
14.8 Conclusions	316	(1)
14.9 Acknowledgements	317	(1)
14.10 References	317