Titlebook: Statistical Signal Processing; Modelling and Estima Thierry Chonavel Textbook 2002 Springer-Verlag London 2002 Estimation.Filtering.Fourier

SCOWL

书目名称Statistical Signal Processing影响因子(影响力)




书目名称Statistical Signal Processing影响因子(影响力)学科排名




书目名称Statistical Signal Processing网络公开度




书目名称Statistical Signal Processing网络公开度学科排名




书目名称Statistical Signal Processing被引频次




书目名称Statistical Signal Processing被引频次学科排名




书目名称Statistical Signal Processing年度引用




书目名称Statistical Signal Processing年度引用学科排名




书目名称Statistical Signal Processing读者反馈




书目名称Statistical Signal Processing读者反馈学科排名

facetious

保守

出血

Statistical Signal Processing978-1-4471-0139-0Series ISSN 1439-2232 Series E-ISSN 2510-3814

合唱队

Non-linear Transforms of Processes,tained in the context of filtering. In fact, studying these relations must generally be done case by case. Here, we present some simple examples of memoryless non-linear transforms that we encounter commonly in the fields of electronics and telecommunications.

Synapse

欺骗手段

Non-parametric Spectral Estimation,ce coefficients are not known exactly but are only estimated. Here, we address the problem of non-parametric estimation of these coefficients, hence that of non-parametric spectral estimation by means of the periodogram estimator.

昏迷状态

Parametric Spectral Estimation,y a small number of autocovariance coefficients of the process being studied are available from the observation. In such situations, parametric spectral estimation techniques are often preferred, and in particular techniques involving rational spectra models.

痛苦一下

Bayesian Methods and Simulation Techniques,or this, we use a Bayesian approach, which allows possible . information about the desired parameters to be incorporated. In order to be able to perform the numerical computation of the estimators, we use Monte Carlo techniques to solve integration and maximisation problems that appear in Bayesian estimation.

胆小鬼

Random Processes,. In this chapter, we recall some notions relating to random processes, looking more particularly at second order properties of processes.