Mobile and wireless application development has come a long way in the past few
years. It has progressed beyond the hype of wireless Web applications for consumers
to the reality of high-value mobile applications for corporate users. Opportunities
abound for creating new mobile and wireless applications that provide vital benefits to
any business. A sampling of these benefits includes increased worker productivity,
reduced processing costs, heightened accuracy, and competitive advantage. In contrast
is the concern that developing mobile and wireless applications will involve many new
technologies and concepts that many corporate developers are still learning to use.
Reliable and accurate positioning and navigation is critical for a diverse set of emerging applications
calling for advanced signal-processing techniques. This book provides an overview of some of the
most recent research results in the field of signal processing for positioning and navigation, addressing
many challenging open problems.
This paper presents a Hidden Markov Model (HMM)-based speech
enhancement method, aiming at reducing non-stationary noise from speech
signals. The system is based on the assumption that the speech and the noise
are additive and uncorrelated. Cepstral features are used to extract statistical
information from both the speech and the noise. A-priori statistical
information is collected from long training sequences into ergodic hidden
Markov models. Given the ergodic models for the speech and the noise, a
compensated speech-noise model is created by means of parallel model
combination, using a log-normal approximation. During the compensation, the
mean of every mixture in the speech and noise model is stored. The stored
means are then used in the enhancement process to create the most likely
speech and noise power spectral distributions using the forward algorithm
combined with mixture probability. The distributions are used to generate a
Wiener filter for every observation. The paper includes a performance
evaluation of the speech enhancer for stationary as well as non-stationary
noise environment.
Smart antennas involve processing of signals induced on an array of sensors such as
antennas, microphones, and hydrophones. They have applications in the areas of radar,
sonar, medical imaging, and communications.
In this thesis several asp ects of space-time pro cessing and equalization for wire-
less communications are treated. We discuss several di?erent metho ds of improv-
ing estimates of space-time channels, such as temp oral parametrization, spatial
parametrization, reduced rank channel estimation, b o otstrap channel estimation,
and joint estimation of an FIR channel and an AR noise mo del. In wireless commu-
nication the signal is often sub ject to intersymb ol interference as well as interfer-
ence from other users.
In this book we focus on the basic signal processing that underlies current and
future ultra wideband systems. By looking at signal processing in this way we
hope this text will be useful even as UWB applications mature and change or
regulations regarding ultra wideband systems are modified. The current UWB
field is extremely dynamic, with new techniques and ideas being presented at every
communications and signal-processing conference. The basic signal-processing
techniques presented in this text though will not change for some time to come.
Thus, we have taken a somewhat theoretical approach, which we believe is longer
lasting and more useful to the reader in the long term than an up-to-the-minute
summary that is out of date as soon as it is published.
Wireless communications, together with its applications and underlying technologies, is
among today’s most active areas of technology development. The very rapid pace of im-
provements in both custom and programmable integrated circuits for signal processing ap-
plications has led to the justfiable view of advanced signal processing as a key enabler of the
aggressively escalating capacity demands of emerging wireless systems. Consequently, there
has been a tremendous and very widespread effort on the part of the research community
to develop novel signal processing techniques that can fulfill this promise.
Digital radios have undergone an astonishing evolution in the last century. Born as a set of simple and
power-hungry electrical and electromechanical devices for low data rate transmission of telegraph data
in the Marconi age, they have transformed, thanks to substantial advances in electronic technology,
into a set of small, reliable and sophisticated integrated devices supporting broadband multimedia
communications. This, however, would not have been possible unless significant progress had been
made in recent decades in the field of signal processing algorithms for baseband and passband signals.
In fact, the core of any modern digital radio consists of a set of algorithms running over programmable
electronic hardware. This book stems from the research and teaching activities of its co-authors in
the field of algorithmic techniques for wireless communications. A huge body of technical literature
has accumulated in the last four decades in this area, and an extensive coverage of all its important
aspects in a single textbook is impossible. For this reason, we have selected a few important topics
and, for ease of reading, organized them into two parts.
In this research, we have designed, developed implemented a wireless sensor
networks based smart home for safe, sound and secured living environment for
any inhabitant especially elderly living alone. We have explored a methodology
for the development of efficient electronic real time data processing system to
recognize the behaviour of an elderly person. The ability to determine the
wellness of an elderly person living alone in their own home using a robust,
flexible and data driven artificially intelligent system has been investigated. A
framework integrating temporal and spatial contextual information for
determining the wellness of an elderly person has been modelled. A novel
behaviour detection process based on the observed sensor data in performing
essential daily activities has been designed and developed.
A power semiconductor module is basically a power circuit of different
materials assembled together using hybrid technology, such as semiconduc-
tor chip attachment, wire bonding, encapsulation, etc. The materials
involved cover a wide range from insulators, conductors, and semiconduc-
tors to organics and inorganics. Since these materials all behave differently
under various environmental, electrical, and thermal stresses, proper selec-
tion of these materials and the assembly processes are critical. In-depth
knowledge of the material properties and the processing techniques is there-
fore required to build a high-performance and highly reliable power module.
