Refine Results
Sort By
From
To
Page 1
Page 1
Linear Estimation and Detection in Krylov Subspaces
Focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems.
Blind Equalization and System Identification : Batch Processing Algorithms, Performance and Applications
Discrete-time signal processing has had a momentous impact on advances in engineering and science over recent decades. The rapid progress of digital and mixed-signal integrated circuits in processing speed, functionality and cost-effectiveness has led to their ubiquitous employment in signal processing and transmission in diverse milieux. Topics covered include: • SISO, MIMO and 2-d non-blind equalization (deconvolution) algorithms. • SISO, MIMO and 2-d blind equalization (deconvolution) algorithms. • SISO, MIMO and 2-d blind system identification algorithms. • algorithm analyses and improvements. • applications of SISO, MIMO and 2-d blind equalization/identification algorithms.
Advanced Fuzzy Logic Technologies in Industrial Applications
Addresses the problem by introducing a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The tuning process is a major focus in this volume because it is the most difficult stage in fuzzy control application. Using new methods such as µ-law technique, histogram equalization and the Bezier-based method, all detailed here, the tuning process can be significantly simplified and control performance improved. The other great strength of this book lies in the range and contemporaneity of its applications and examples which include: laser tracking and control; robot calibration; image processing and pattern recognition; medical engineering; audio systems; autonomous underwater vehicles and data mining.
Adaptive Techniques for Mixed Signal System on Chip
Adaptive Techniques for Mixed Signal Sytem on Chip discusses the concept of adaptation in the context of analog and mixed signal design along with different adaptive architectures used to control any system parameter. The first part of the book gives an overview of the different elements that are normally used in adaptive designs including tunable elements as well as voltage, current, and time references with an emphasis on the circuit design of specific blocks such as voltage-controlled transconductors, offset comparators, and a novel technique for accurate implementation of on chip resistors. While the first part of the book addresses adaptive techniques at the circuit and block levels, the second part discusses adaptive equalization architectures employed to minimize the impact of ISI (Intersymbol Interference) on the quality of received data in high-speed wire line transceivers. It presents the implementation of a 125Mbps transceiver operating over a variable length of Category 5 (CAT-5) Ethernet cable as an example of adaptive equalizers.
