By Abdelhak M. Zoubir, Mats Viberg, Rama Chellappa and Sergios Theodoridis (Eds.)
This 3rd quantity of a 5 quantity set, edited and authored through global major specialists, provides a overview of the foundations, equipment and methods of vital and rising examine subject matters and applied sciences in array and statistical sign processing.
With this reference resource you will:
- Quickly snatch a brand new sector of research
- Understand the underlying ideas of an issue and its application
- Ascertain how an issue pertains to different parts and research of the learn concerns but to be resolved
- Quick instructional stories of vital and rising issues of analysis in array and statistical sign processing
- Presents center ideas and indicates their application
- Reference content material on center ideas, applied sciences, algorithms and functions
- Comprehensive references to magazine articles and different literature on which to construct extra, extra particular and exact wisdom
- Edited by means of leading people in the sector who, via their attractiveness, were capable of fee specialists to put in writing on a specific topic
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Additional info for Array and Statistical Signal Processing
Notations. More specifically, model selection refers to the multihypothesis testing problem of determining which model best describes a given data (measurement) y of size N. Let Hm , m = 1, . . ) f m with a parameter vector θ of dimension K = dim(θ |Hm ) in the parameter space . For the notational convenience we often suppress the subscript m (the model index) from θ, K , and but the reader should keep in mind that these differ for each model. 2 Example: Variable Selection in Regression 11 the nested set of hypotheses.
References 25  P. Kontkanen, W. Buntine, P. Myllymaki, J. Rissanen, H. Tirri, Efficient computation of stochastic complexity, in: Proceedings of International Conference on Artificial Intelligence and, Statistics, 2003, pp. 233–238. C. R. D. Bai, On detection of the number of signals in presence of white noise, J. Multivar. Anal. 20 (1) (1986) 1–25.  M. Novey, E. Ollila, T. Adali, On testing the extent of noncircularity, IEEE Trans. Signal Process. 59 (11) (2011) 5632–5637. W. Anderson, Asymptotic theory for principal component analysis, Ann.
Adali, On testing the extent of noncircularity, IEEE Trans. Signal Process. 59 (11) (2011) 5632–5637. W. Anderson, Asymptotic theory for principal component analysis, Ann. Math. Stat. 1 (1963) 122–148. 1 Introduction The Fourier transform (FT) provides a unique mapping of a signal from the time domain to the frequency domain. The frequency domain representation provides the signal’s spectral content. Although the phase characteristic of the FT contains information about the time distribution of the spectral content, it is very difficult to use this information.