Topic
Multidimensional signal processing
About: Multidimensional signal processing is a research topic. Over the lifetime, 5408 publications have been published within this topic receiving 161456 citations.
Papers published on a yearly basis
Papers
More filters
•
17 Dec 2015
TL;DR: Time Frequency Signal Analysis and Processing focuses on advanced techniques and methods that allow a refined extraction and processing of information, allowing efficient and effective decision making that would not be possible with classical techniques.
Abstract: Time Frequency Signal Analysis and Processing covers fundamental concepts, principles and techniques, treatment of specialised and advanced topics, methods and applications, including results of recent research. This book deals with the modern methodologies, key techniques and concepts that form the core of new technologies used in IT, multimedia, telecommunications as well as most fields of engineering, science and technology. It focuses on advanced techniques and methods that allow a refined extraction and processing of information, allowing efficient and effective decision making that would not be possible with classical techniques.
1,130 citations
•
01 Jan 1992
TL;DR: Applications of transforms in signal processing signal processing in subbands lapped orthogonal transforms the modulated lapped transform heirarchical lapped transforms applications of lapping transforms.
Abstract: Applications of transforms in signal processing signal processing in subbands lapped orthogonal transforms the modulated lapped transform heirarchical lapped transforms applications of lapped transforms.
1,071 citations
•
01 Jun 1993
TL;DR: This book covers a number of DSP techniques that are of particular relevance to industry such as adaptive filtering and multirate processing, and offers modern coverage of the fundamentals, implementation and applications of digital signal processing techniques from a practical point of view.
Abstract: From the Publisher:
Now in its second edition, Digital Signal Processing offers modern coverage of the fundamentals, implementation and applications of digital signal processing techniques from a practical point of view. The past ten years have seen a significant growth in DSP applications throughout all areas of technologyand this growth is expected well into the next millennium. This book covers a number of DSP techniques that are of particular relevance to industry such as adaptive filtering and multirate processing. The emphasis throughout the book is on the practical aspects of DSP. Chapter topics include analogue I/O interface for real-time DSP systems, discrete transform, the z-transform and its applications in signal processing, correlation and convolution, a framework for digital filter design, finite impulse response (FIR) filter design, design of infinite impulse response (IIR) digital filters, multirate digital signal processing, adaptive digital filters, spectrum estimation and analysis, general and special purpose hardware for DSP, and finite word length effects in fixed point DSP systems and solutions. A reference of DSP techniques for industry professionals.
1,064 citations
••
01 Jul 1993TL;DR: A tutorial review of the basic characteristics of stable distributions and stable signal processing is presented, focusing on the differences and similarities between stable signal processors based on fractional lower-order moments and Gaussian signal processing methods based on second-order Moments.
Abstract: Non-Gaussian statistical signal processing is important when signals and/or noise deviate from the ideal Gaussian model. Stable distributions are among the most important non-Gaussian models. They share defining characteristics with the Gaussian distribution, such as the stability property and central limit theorems, and in fact include the Gaussian distribution as a limiting case. To help engineers better understand the stable models and develop methodologies for their applications in signal processing. A tutorial review of the basic characteristics of stable distributions and stable signal processing is presented. The emphasis is on the differences and similarities between stable signal processing methods based on fractional lower-order moments and Gaussian signal processing methods based on second-order moments. >
964 citations
••
01 Nov 1977TL;DR: The effects of modifications made to the short-time transform are explicitly shown on the resulting signal and it is shown that a formal duality exists between the two synthesis methods based on the properties of the window used for obtaining theshort-time Fourier transform.
Abstract: Two distinct methods for synthesizing a signal from its short-time Fourier transform have previously been proposed. We call these methods the filter-bank summation (FBS) method and the overlap add (OLA) method. Each of these synthesis techniques has unique advantages and disadvantages in various applications due to the way in which the signal is reconstructed. In this paper we unify the ideas behind the two synthesis techniques and discuss the similarities and differences between these methods. In particular, we explicitly show the effects of modifications made to the short-time transform (both fixed and time-varying modifications are considered) on the resulting signal and discuss applications where each of the techniques would be most useful The interesting case of nonlinear modifications (possibly signal dependent) to the short-time Fourier transform is also discussed. Finally it is shown that a formal duality exists between the two synthesis methods based on the properties of the window used for obtaining the short-time Fourier transform.
954 citations