Gør som tusindvis af andre bogelskere
Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.
Ved tilmelding accepterer du vores persondatapolitik.Du kan altid afmelde dig igen.
This sep aration is of more than academic interest as the least squares problem leads to the normal equations, which are numerically ill conditioned, while the process estimation problem in the linear case with appropriate assumptions leads to uniformly asymptotically stable equations for the estimator and the gain.
This graduate-level text provides a language for understanding, unifying, and implementing a wide variety of algorithms for digital signal processing - in particular, to provide rules and procedures that can simplify or even automate the task of writing code for the newest parallel and vector machines.
Many of the techniques of digital signal processing are valid in any algebraic field, although in most cases at least part of the problem will naturally lie either in the real field or the complex field because that is where the data originate.
Earlier approaches to MLD, which are couched in the language of state-variable models and estimation theory, are unnecessary to understand the essence of MLD. MLD is a model-based signal processing procedure, because it is based on a signal model, namely the convolutional model.
This book is intended as an introduction to array signal process ing, where the principal objectives are to make use of the available multiple sensor information in an efficient manner to detect and possi bly estimate the signals and their parameters present in the scene.
Of special interest are the surface mapping radars, such as the Seasat and the shuttle imaging radars, which utilize a technique known as synthetic aperture radar (SAR) to create high resolution images (pic tures).
Developing algorithms for multi-dimensional Fourier transforms, this book presents results that yield highly efficient code on a variety of vector and parallel computers.
This book is intended to be a comprehensive reference to multiplicative com plexity theory as applied to digital signal processing computations. Although a few algorithms are included to illustrate the theory, I concentrated more on the develop ment of the theory itself.
Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.
Ved tilmelding accepterer du vores persondatapolitik.