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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 the signal.
Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals, such as sound, images, potential fields, seismic signals, altimetry processing, and scientific measurements. [1] Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted ...
The following terms are used by electrical engineers in statistical signal processing studies instead of typical statistician's terms. Statistics. Electrical engineering. Null hypothesis. Noise only hypothesis. Alternative hypothesis. Signal + noise hypothesis. Critical region. Signal present decision region.
Kay, S. M. (1993). Fundamentals of Statistical Signal Processing: ... Mathematical Methods and Algorithms for Signal Processing. Prentice-Hall. ISBN ...
Detection theory or signal detection theory is a means to measure the ability to differentiate between information-bearing patterns (called stimulus in living organisms, signal in machines) and random patterns that distract from the information (called noise, consisting of background stimuli and random activity of the detection machine and of the nervous system of the operator).
In signal processing, undersampling or bandpass sampling is a technique where one samples a bandpass -filtered signal at a sample rate below its Nyquist rate (twice the upper cutoff frequency), but is still able to reconstruct the signal.
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 ...
Empirical orthogonal functions. In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data. The term is also interchangeable with the geographically weighted Principal components analysis in ...