Обработка сигналов
Радиоэлектроника
  • формат pdf
  • размер 27.08 МБ
  • добавлен 21 ноября 2011 г.
Zaher A.A. (ed.) Recent Advances in Signal Processing
Издательство InTech, 2009, -558 pp.

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This was mainly due to the revolutionary advances in the digital technology and the ability to effectively use digital signal processing (DSP) that rely on the use of very large scale integrated technologies and efficient computational methods such as the fast Fourier transform (FFT). This trend is expected to grow exponentially in the future, as more and more emerging technologies are revealed in the fields of digital computing and software development.
It is still an extremely skilled work to properly design, build and implement an effective signal processing tool able to meet the requirements of the increasingly demanding and sophisticated mode applications. This is especially true when it is necessary to deal with real-time applications of huge data rates and computational loads. These applications include image compression and encoding, speech analysis, wireless communication systems, biomedical real-time data analysis, cryptography, steganography, and biometrics, just to name a few. Moreover, the choice between whether to adopt a software or hardware approach, for implementing the application at hand, is considered a bottleneck. Programmable logic devices, e.g. FPGAs provide an optimal compromise, as the hardware configuration can be easily tailored using specific hardware descriptive languages (HDLs).
This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand.
These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity. Each chapter provides a comprehensive survey of the subject area and terminates with a rich list of references to provide an in-depth coverage of the application at hand. Understanding the fundamentals of representing signals and systems in both time, spatial, and frequency domains is a prerequisite to read this book, as it is assumed that the reader is familiar with them. Knowledge of other transform methods, such as the Laplace transform and the Z-transform, along with knowledge of some computational intelligence techniques is an assist. In addition, experience with MATLAB programming (or a similar tool) is useful, but not essential. This book is application-oriented and it mainly addresses the design, implementation, and/or the improvements of existing or new technologies, and also provides some novel algorithms either in software, hardware, or both forms. The reported techniques are based on time-domain analysis, frequency-domain analysis, or a hybrid combination of both.

Digital Image Stabilization.
About array processing methods for image segmentation.
Locally Adaptive Resolution (LAR) codec.
Methods for Nonlinear Intersubject Registration in Neuroscience.
Functional semi-automated segmentation of renal DCE-MRI sequences using a Growing Neural Gas algorithm.
Combined myocardial motion estimation and segmentation using variational techniques.
Protecting the color information by hiding it.
JPEG2000-Based Data Hiding and its Application to 3D Visualization.
Content-Based Image Retrieval as Validation for Defect Detection in Old Photos.
Supervised Crack Detection and Classification in Images of Road Pavement Flexible Surfaces.
Contact-free hand biometric system for real environments based on geometric features.
Gaze prediction improvement by adding a face feature to a saliency model.
Suppression of Correlated Noise.
Noise Estimation of Polarization-Encoded Images by Peano-Hilbert Fractal Path.
Speech Enhancement based on Iterative Wiener Filter using Complex LPC Speech Analysis.
Detection of echo generated in mobile phones.
Application of the Vector Quantization Methods and the Fused MFCC-IMFCC Features in the GMM based Speaker Recognition.
Information Mining from Speech Signal.
Estimation of the instantaneous harmonic parameters of speech.
Music Structure Analysis Statistics for Popular Songs.
MIMO Channel Modeling and Simulation.
On the role of receiving beamforming in transmitter cooperative communications.
Robust Designs of Chaos-Based Secure Communication Systems.
Simultaneous EEG-fMRI Analysis with Application to Detection of Seizure Signal Sources.
Real-Time Signal Acquisition, High Speed Processing and Frequency Analysis in Mode Air Data Measurement Instruments.
Performance analysis of port-starboard discrimination for towed multi-line array.
Audio and Image Processing Easy Leaing for Engineering.
Похожие разделы
Смотрите также

Allen J.B., Chan W.-Y.G., Voran S. (eds.) Perceptual Models for Speech, Audio, and Music Processing

  • формат pdf
  • размер 7.71 МБ
  • добавлен 20 января 2012 г.
EURASIP Journal on Audio, Speech, and Music Processing, 2007, -92 pp. New understandings of human auditory perception have recently contributed to advances in numerous areas related to audio, speech, and music processing. These include coding, speech and speaker recognition, synthesis, signal separation, signal enhancement, automatic content identification and retrieval, and quality estimation. Researchers continue to seek more detailed, accurat...

Barner K.E., Arce G.R. Nonlinear Signal and Image Processing. Theory, Methods, and Applications

  • формат pdf
  • размер 30.43 МБ
  • добавлен 28 июня 2011 г.
Издательство CRC Press, 2004, -535 pp. Книга из серии «The Electrical Engineering and Applied Signal Processing Series» Nonlinear signal processing methods continue to grow in popularity and use. This growth is due to one factor—performance. While it is true that linear methods continue to dominate in current practice, nonlinear methods are making steady progress in moving from theoretical explorations to practical implementations. Clearly, the...

Bose N.K., Rao C.R. (eds.) Handbook of Statistics 10: Signal Processing and its Applications

  • формат djvu
  • размер 8.99 МБ
  • добавлен 29 ноября 2011 г.
Elsеvier Sciеnce, 1993. - 992 pages. This volume of the "Handbook of Statistics" emphasizes both theory and applications. The collection of chapters deals with the topics of fast computations and transforms in signal processing, sampling theorems, parameter estimation and signal modelling, image and multidimensional signal processing, array processing, direction-of-arrival estimation, beamforming, adaptive algorithms, multiscale signal processi...

Cichocki A., Amari S. Adaptive Blind Signal and Image Processing

  • формат pdf
  • размер 24.01 МБ
  • добавлен 07 июля 2011 г.
Издательство John Wiley, 2000, -587 pp. Signal processing has always played a critical role in science and technology and development of new systems like computer tomography, wireless communication, digital cameras etc. As demand of high quality and reliability in recording and visualization systems increases, signal processing has an even more important role to play. Blind signal processing is now one if the hottest and emerging areas in signal...

Klapuri A., Davy M. Signal Processing Methods for Music Transcription

  • формат pdf
  • размер 24.89 МБ
  • добавлен 03 августа 2011 г.
Издательство Springer, 2006, -443 pp. Signal processing techniques, and information technology in general, have undergone several scientific advances which permit us to address the very complex problem of automatic music transcription (AMT). During the last ten years, the interest in AMT has increased rapidly, and the time has come for a book-length overview of this subject. The purpose of this book is to present signal processing algorithms ded...

Marshall S., Sicuranza G.L. Advances in Nonlinear Signal and Image Processing

  • формат pdf
  • размер 18.79 МБ
  • добавлен 05 августа 2011 г.
Marshall S., Sicuranza G.L. Advances in Nonlinear Signal and Image Processing. Издательство Hindawi, 2006, 367 c. n recent years the area of nonlinear signal and image processing has emerged as a distinct research field in its own right. It has formed from a fusion of techniques which, whilst coming from very different sources, share many characteristics. These techniques have appeared for two main reasons: (i) the availability of high-powered c...

Miron S. (ed.) Signal Processing

  • формат pdf
  • размер 19.45 МБ
  • добавлен 21 ноября 2011 г.
Издательство InTech, 2010, -536 pp. The exponential development of sensor technology and computer power over the last few decades, transformed signal processing in an essential tool for a wide range of domains such as telecommunications, medicine or chemistry. Signal processing plays nowadays a key role in the progress of knowledge, from the discoveries on the universe underlying structure, to the recent breakthroughs in the understanding of th...

Najim M. Digital Filters Design for Signal and Image Processing

  • формат pdf
  • размер 4.99 МБ
  • добавлен 05 августа 2011 г.
Издательство ISTE, 2006, -386 pp. Over the last decade, digital signal processing has matured; thus, digital signal processing techniques have played a key role in the expansion of electronic products for everyday use, especially in the field of audio, image and video processing. Nowadays, digital signal is used in MP3 and DVD players, digital cameras, mobile phones, and also in radar processing, biomedical applications, seismic data processing,...

Rockmore D.N., Healy D.M. (editors) Modern Signal Processing

  • формат pdf
  • размер 6.9 МБ
  • добавлен 29 января 2011 г.
Cambridge University Press, 2010. - 346 pages. Signal processing is ubiquitous in modern technology. Its mathematical basis and many areas of application are the subject of this book, based on a series of graduate-level lectures held at the Mathematical Sciences Research Institute. Emphasis is on current challenges, new techniques adapted to new technologies, and certain recent advances in algorithms and theory. rn

White S. Digital Signal Processing. A Filtering Approach

  • формат pdf
  • размер 3.28 МБ
  • добавлен 09 августа 2011 г.
Издательство Delmar, 2000, -229 pp. Digital signal processing (DSP) refers to anything that can be done to a signal using code on a computer or DSP chip. To reduce certain sinusoidal frequency components in a signal in amplitude, digital filtering is done. One may want to obtain the integral of a signal. If the signal comes from a tachometer, the integral gives the position. If the signal is noisy, then filtering the signal to reduce the amplitu...