Ads
related to: statistical signal processing
Search results
Results From The WOW.Com Content Network
Statistical techniques are widely used in signal processing applications. For example, one can model the probability distribution of noise incurred when photographing an image, and construct techniques based on this model to reduce the noise in the resulting image.
Pages in category "Statistical signal processing" The following 23 pages are in this category, out of 23 total. This list may not reflect recent changes. B.
In statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the power spectral density) of a signal from a sequence of time samples of the signal. [1] Intuitively speaking, the spectral density characterizes the frequency content of
Hjorth parameters are indicators of statistical properties used in signal processing in the time domain introduced by Bo Hjorth in 1970. [1] The parameters are Activity, Mobility, and Complexity. They are commonly used in the analysis of electroencephalography signals for feature extraction. The parameters are normalised slope descriptors (NSDs ...
In statistics and signal processing, step detection (also known as step smoothing, step filtering, shift detection, jump detection or edge detection) is the process of finding abrupt changes (steps, jumps, shifts) in the mean level of a time series or signal.
The origins of SSA and, more generally, of subspace-based methods for signal processing, go back to the eighteenth century (Prony's method).A key development was the formulation of the spectral decomposition of the covariance operator of stochastic processes by Kari Karhunen and Michel Loève in the late 1940s (Loève, 1945; Karhunen, 1947).
His research interests lie in the areas of stochastic analysis, statistical signal processing and information theory, and their applications in a number of fields including wireless networks, social networks, and smart grid. This research work has attracted over 10,000 citations. [10] He has published a book on Signal Detection and Estimation. [11]
The general ARMA model was described in the 1951 thesis of Peter Whittle, who used mathematical analysis (Laurent series and Fourier analysis) and statistical inference. [ 12 ] [ 13 ] ARMA models were popularized by a 1970 book by George E. P. Box and Jenkins, who expounded an iterative ( Box–Jenkins ) method for choosing and estimating them.