Search results
Results From The WOW.Com Content Network
The Nyquist–Shannon sampling theorem is an essential principle for digital signal processing linking the frequency range of a signal and the sample rate required to avoid a type of distortion called aliasing. The theorem states that the sample rate must be at least twice the bandwidth of the signal to avoid aliasing.
In probability theory, the optional stopping theorem (or sometimes Doob's optional sampling theorem, for American probabilist Joseph Doob) says that, under certain conditions, the expected value of a martingale at a stopping time is equal to its initial expected value. Since martingales can be used to model the wealth of a gambler participating ...
Papoulis's generalization of the sampling theorem [6] unified many variations of the Nyquist–Shannon sampling theorem into one theorem. [7] [8] The Papoulis–Gerchberg algorithm [9] [10] [11] is an iterative signal restoration algorithm that has found widespread use in signal and image processing. [12] [13]
The misconceived belief that the theorem applies to random sampling of any variable, rather than to the mean values (or sums) of iid random variables extracted from a population by repeated sampling. That is, the theorem assumes the random sampling produces a sampling distribution formed from different values of means (or sums) of such random ...
Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov transform) is a basic method for pseudo-random number sampling, i.e., for generating sample numbers at random from any probability distribution given its cumulative distribution function.
The more things change … Granted, change wasn’t universal. For all the upheavals in college football and the WNBA, plenty of old-school blue bloods added more trophies to their already massive ...
A general proof of this was given by Halmos and Savage [6] and the theorem is sometimes referred to as the Halmos–Savage factorization theorem. [7] The proofs below handle special cases, but an alternative general proof along the same lines can be given. [8]
From January 2008 to December 2012, if you bought shares in companies when Albert C. Zapanta joined the board, and sold them when he left, you would have a 27.4 percent return on your investment, compared to a -2.8 percent return from the S&P 500.