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  2. Gambling mathematics - Wikipedia

    en.wikipedia.org/wiki/Gambling_mathematics

    The mathematics of gambling is a collection of probability applications encountered in games of chance and can get included in game theory.From a mathematical point of view, the games of chance are experiments generating various types of aleatory events, and it is possible to calculate by using the properties of probability on a finite space of possibilities.

  3. Nonuniform sampling - Wikipedia

    en.wikipedia.org/wiki/Nonuniform_sampling

    Nonuniform sampling is a branch of sampling theory involving results related to the Nyquist–Shannon sampling theorem. Nonuniform sampling is based on Lagrange interpolation and the relationship between itself and the (uniform) sampling theorem. Nonuniform sampling is a generalisation of the Whittaker–Shannon–Kotelnikov (WSK) sampling theorem.

  4. Oversampling - Wikipedia

    en.wikipedia.org/wiki/Oversampling

    The sampling theorem states that sampling frequency would have to be greater than 200 Hz. Sampling at four times that rate requires a sampling frequency of 800 Hz. This gives the anti-aliasing filter a transition band of 300 Hz ((f s /2) − B = (800 Hz/2) − 100 Hz = 300 Hz) instead of 0 Hz if the sampling frequency was 200 Hz. Achieving an ...

  5. Nyquist–Shannon sampling theorem - Wikipedia

    en.wikipedia.org/wiki/Nyquist–Shannon_sampling...

    The term Nyquist Sampling Theorem (capitalized thus) appeared as early as 1959 in a book from his former employer, Bell Labs, [22] and appeared again in 1963, [23] and not capitalized in 1965. [24] It had been called the Shannon Sampling Theorem as early as 1954, [25] but also just the sampling theorem by several other books in the early 1950s.

  6. Optional stopping theorem - Wikipedia

    en.wikipedia.org/wiki/Optional_stopping_theorem

    Now consider a random walk X that starts at 0 and stops if it reaches –m or +m, and use the Y n = X n 2 – n martingale from the examples section. If τ is the time at which X first reaches ±m, then 0 = E[Y 0] = E[Y τ] = m 2 – E[τ]. This gives E[τ] = m 2. Care must be taken, however, to ensure that one of the conditions of the theorem ...

  7. Simple random sample - Wikipedia

    en.wikipedia.org/wiki/Simple_random_sample

    It is a process of selecting a sample in a random way. In SRS, each subset of k individuals has the same probability of being chosen for the sample as any other subset of k individuals. [1] Simple random sampling is a basic type of sampling and can be a component of other more complex sampling methods. [2]