Support Vector Machines for Antenna Array Processing and Electromagnetics,by: Manel Martinez-Ramon and Christos Cristodoulou,Copyright 2006 by Morgan and Claypool.this book is one of the best books about svm. it has some excellent example in matlab.
Implementation of GPU (Graphics Processing Unit) that rendered triangle based models. Our goal was to generate complex models with a movable camera. We wanted to be able to render complex images that consisted of hundreds to thousands of triangles. We wanted to apply interpolated shading on the objects, so that they appeared more
smooth and realisitc, and to have a camera that orbitted around the object, which allowed us to
look arond the object with a stationary light source. We chose to do this in hardware, because our initial implementation using running software on the NIOS II processor was too slow. Implementing parallelism in hardware is also easier to do than in software, which allows for more efficiency. We used Professor Land s floating point hardware, which allowed us to do calculations efficiency, which is essential to graphics.
Sha256 Algorithm. The SHA hash functions are a set of cryptographic hash functions designed by the National Security Agency (NSA) and published by the NIST as a U.S. Federal Information Processing Standard. SHA stands for Secure Hash Algorithm
The OpenMAX DL (Development Layer) APIs contain a comprehensive set of audio, video, signal processing function primitives which can be implemented and optimized on various CPUs and hardware engines and then used for accelerated codec functionality. API functions target key algorithms in such codecs as H.264, MPEG-4, AAC, MP3, and JPEG.
Multiple-Input Multiple-Output (MIMO) systems have recently been the
subject of intensive consideration in modem wireless communications as they
offer the potential of providing high capacity, thus unleashing a wide range of
applications in the wireless domain. The main feature of MIMO systems is the
use of space-time processing and Space-Time Codes (STCs). Among a variety
of STCs, orthogonal Space-Time Block Codes (STBCs) have a much simpler
decoding method, compared to other STCs
Driven by the desire to boost the quality of service of wireless systems closer to that afforded
by wireline systems, space-time processing for multiple-input multiple-output (MIMO)
wireless communications research has drawn remarkable interest in recent years. Excit-
ing theoretical advances, complemented by rapid transition of research results to industry
products and services, have created a vibrant and growing area that is already established
by all counts. This offers a good opportunity to reflect on key developments in the area
during the past decade and also outline emerging trends.
The goal of this textbook is to support the teaching of digital and statistical signal
processing in higher education. Particular attention is paid to the presentation of the fun-
damental theory; key topics are outlined in a comprehensible way, and all areas of the
subject are discussed in a fashion that aims at simplification without sacrificing accuracy.
Artificial Intelligence (AI) has undoubtedly been one of the most important buz-
zwords over the past years. The goal in AI is to design algorithms that transform com-
puters into “intelligent” agents. By intelligence here we do not necessarily mean an
extraordinary level of smartness shown by superhuman; it rather often involves very
basic problems that humans solve very frequently in their day-to-day life. This can
be as simple as recognizing faces in an image, driving a car, playing a board game, or
reading (and understanding) an article in a newspaper. The intelligent behaviour ex-
hibited by humans when “reading” is one of the main goals for a subfield of AI called
Natural Language Processing (NLP). Natural language 1 is one of the most complex
tools used by humans for a wide range of reasons, for instance to communicate with
others, to express thoughts, feelings and ideas, to ask questions, or to give instruc-
tions. Therefore, it is crucial for computers to possess the ability to use the same tool
in order to effectively interact with humans.
This edition of Digital Image Processing is a major revision of the book. As in
the 1977 and 1987 editions by Gonzalez and Wintz, and the 1992, 2002, and 2008
editions by Gonzalez and Woods, this sixth-generation edition was prepared
with students and instructors in mind. The principal objectives of the book
continue to be to provide an introduction to basic concepts and methodologies
applicable to digital image processing, and to develop a foundation that can
be used as the basis for further study and research in this field. To achieve
these objectives, we focused again on material that we believe is fundamental
and whose scope of application is not limited to the solution of specialized
problems. The mathematical complexity of the book remains at a level well
within the grasp of college seniors and first-year graduate students who have
introductory preparation in mathematical analysis, vectors, matrices, probability,
statistics, linear systems, and computer programming. The book website provides
tutorials to support readers needing a review of this background material
