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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.
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.
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.
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.
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