Now-a-days, wireless communications gets more attention from the Communication industry and provide quality information transfer between portable devices.Applications like Autonomous sensor networks, Multimedia, Videoconferencing, and Distance learning and Internet enabled cell phone are developed by 3G system. Also Long Term Evolution (LTE) is going to increase the data rate, throughput, decrease latency, etc, for the above applications and also to bring lot of applications. Our primary aim of this book is to minimize the error probability of a LTE system and to bring the spectrum efficiency through a process known as adaptive modulation and coding rate. Chapter 1 introduces the features of fourth generation communication systems. Chapter 2 discusses about Literature review of OFDM, CDMA LTE systems. Chapter 3 analyses the OFDM in AWGN channel for different modulation techniques. Results are discussed in Chapter 4. Chapter 5 brings out the conclusion. This monograph is useful for all Engineering undergraduate, graduates students and practicing engineers.

This book emphasizes on a Field Programmable Gate Array (FPGA) Implementation of Fuzzy PD and PID Controller for biomedical application. A novel approach aims to identify and design a simple robust Fuzzy (PD and PID) Controller system with minimum number of fuzzy rules to deliver insulin from pumps as a single injection process for the diabetic patients. This controller is an automatic feedback control system in which the patient's blood glucose level is monitored from non-invasive Photo plethysmogram of a pulse oximeter (Photoglucometer) and insulin is infused with the change in the glucose level of the diabetic patient. This work was carried out in three phases like phase -I VLSI Design and simulation of Fuzzy PD controller were performed and analyzed. From the VLSI Simulation results FPGA Model was synthesized in the phase-II. During phase -III performance of the fuzzy PD Controller was evaluated. VLSI fuzzy system was simulated and analyzed then FPGA module was synthesized and implemented using VHDL.A part of this work was sponsored by IEEE Inc., (U.S.A) under scheme IEEE Student Enterprise Award 2007-2008 title FPGA Model of Fuzzy PD Controller for Insulin Pumps In Diabetes.

Epileptic seizures result from a sudden electrical disturbance to the brain. Approximately one in every 100 persons will experience a seizure at some time in their life. In this work, we propose a genetic algorithm, SVM based fuzzy knowledge integration framework that is used for classification of risk level of epilepsy in diabetic patients from Electroencephalogram (EEG) signals. A statistical analysis of the EEG signal to indicate the onset of epilepsy based on chi square tests and control limits. Ten known diabetic patients with raw EEG recording are studied. Chapter 1 introduces the features of EEG signals and focus of the research. Chapter 2 discusses about Statistical analysis and quantification of Diabetic epilepsy risk through Chi-square tests. Chapter 3 reviews the fundamentals of fuzzy systems. Chapter 4 enumerates the Genetic algorithms for optimization of epilepsy risk levels. SVM techniques as a post classifier for epilepsy detection are discussed in Chapter 5. Results are discussed in Chapter 6. Chapter 7 brings out the conclusion. Chapter 8 shows the Future scope. This monograph is useful for all Engineering undergraduate, graduates students and practicing engineers.

Digital Image Processing and Medical Image Processing present an exciting and dynamic part of cognitive and pattern recognition techniques. Diagnostic applications of medical images are very exciting and they throw more insight about segmentation algorithms. This monograph reflects an introductory methodology for medical image segmentation using k-means clustering and subsequent optimization of clusters by means of EM and SVD. Chapter 1 introduces the need for segmentation of medical images and focus of the research. Chapter 2 discusses the general clustering algorithm and chapter 3 discusses the review of K-means clustering algorithm, EM models for optimization of clusters are analyzed in chapter 4. SVD optimization techniques are elucidated in the chapter 5. chapter 6 shows the overall results and discussion of this work. This monograph is concluded in chapter 7.To achieve a complete segmentation, cooperation with higher processing levels which use specific knowledge of the problem domain is necessary. This monograph is useful for all Engineering undergraduate and graduates students specializing in ECE, EEE, and computer science. This monograph will be useful reference.

The EEG signals are highly subjective and the information about the various states may appear at random in the time scale. For example, a time series may be obtained by recording at regular time intervals the mean electrical activity of a portion of the mammalian brain. More specifically, by using a time series one can determine the possibility of constructing an attractor and thereby establishing the deterministic character of dynamic underlying system. Such methods from the non linear dynamical theory can be dragged for better perception of EEG signals. The complexity of drowsiness estimation and characterizing the EEG signals can be brought under some chaotic optimization techniques. Chapter1 introduces Chaos, Non linear dynamics and focus of the research. Chapter 2 discusses the literature survey of correlation dimension estimation. Chapter 3 and Chapter 4 enumerate the review of LAB view and Mat lab software for the book. Results are discussed in Chapter 5. Chapter 6 brings out the conclusion of this work. Future scope of this work is solemnized in chapter 7. This monograph is useful for all Engineering undergraduate, graduates students and practicing engineers.