Open AccessBook
Fundamentals Of Statistical Signal Processing
About:
The article was published on 2001-03-16 and is currently open access. It has received 7058 citations till now. The article focuses on the topics: Statistical signal processing.read more
Citations
More filters
Dissertation
Space-Time Codes for High Data Rate Wireless Communications
TL;DR: Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding.
Journal ArticleDOI
Detection algorithms for hyperspectral imaging applications
Dimitris G. Manolakis,G. Shaw +1 more
TL;DR: This work focuses on detection algorithms that assume multivariate normal distribution models for HSI data and presents some results which illustrate the performance of some detection algorithms using real hyperspectral imaging (HSI) data.
Journal ArticleDOI
Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels
TL;DR: In this article, the authors formalize the notion of multipath sparsity and present a new approach to estimate sparse (or effectively sparse) multipath channels that is based on some of the recent advances in the theory of compressed sensing.
Posted Content
Eigenvalue based Spectrum Sensing Algorithms for Cognitive Radio
Yonghong Zeng,Ying-Chang Liang +1 more
TL;DR: In this article, the eigenvalues of the covariance matrix of signals received at the secondary users are used for signal detection in cognitive radio systems, and the proposed methods overcome the noise uncertainty problem, and can even perform better than the ideal energy detection when the signals to be detected are highly correlated.
Journal ArticleDOI
Optimal designs for space-time linear precoders and decoders
TL;DR: A new paradigm for the design of transmitter space-time coding is introduced that is referred to as linear precoding, which leads to simple closed-form solutions for transmission over frequency-selective multiple-input multiple-output (MIMO) channels, which are scalable with respect to the number of antennas, size of the coding block, and transmit average/peak power.
References
More filters
Book
Statistical Signal Processing: Modelling and Estimation
T. Chonavel,Janet Ormrod +1 more
TL;DR: In this article, Kolmogorov's Isomorphism and Spectral Representation of WSS Processes were used to identify WSS processes and their spectral properties, and a linear operator was used to estimate the spectral properties of Wss processes.
Proceedings ArticleDOI
Channel identification using second order cyclic statistics
TL;DR: It is shown that channel identification is achievable for a class of linear channels without the need for a pilot tone or training periods and does not preclude Gaussian or near-Gaussian inputs.
Proceedings ArticleDOI
HOS or SOS for parametric modeling
TL;DR: To quantify normality and time-reversibility, consistent, time-domain statistical tests are developed and analyzed in a Neyman-Pearson framework and employ the minimal HOS lags which uniquely characterize autoregressive moving-average processes.
Journal ArticleDOI
A bibliography of higher-order spectra and cumulants
P.A. Delaney,D.O. Walsh +1 more
TL;DR: The interest in higher-order spectra and cumulants was renewed in the early 1980s due, in part, to the need to solve detection, estimation, and identification problems when the interfering noise source was non-Gaussian.
Journal ArticleDOI
Fourier series based nonminimum phase model for statistical signal processing
TL;DR: An iterative algorithm for obtaining the optimum LPE filter with finite data is presented that is also an approximate maximum-likelihood algorithm when data are Gaussian and three iterative algorithms using higher order statistics with finite non-Gaussian data are presented to estimate parameters of the FSBM.