Download A First Course in Statistics for Signal Analysis by Wojbor A. Woyczynski PDF

By Wojbor A. Woyczynski

This article serves as a good advent to stats for sign research. remember that it emphasizes concept over numerical equipment - and that it really is dense. If one isn't really searching for long factors yet as an alternative desires to get to the purpose fast this publication could be for them.

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Extra resources for A First Course in Statistics for Signal Analysis

Example text

2) holds true. Uniform approximation in time t. If one wants to control the error of approximation simultaneously (uniformly) for all times t, then more stringent assumptions on the signal are necessary. , T. W. Körner, Fourier Analysis, Cambridge University Press, Cambridge, UK, 1988. 28 2 Spectral Representation of Deterministic Signals If the signal is continuous everywhere and has a bounded continuous derivative except at a finite number of points, then max |x(t) − sM (t)| → 0 0≤t≤P as M → ∞.

2k + 1) π (2k + 1) Thus the complex Fourier expansion of the signal x(t) is x(t) = a a + 2 π ∞ (−1)k j2π (2k+1)t/P e . 2k + 1 k=−∞ Observe that for any m = . . , −1, 0, 1, . . , we have zm = z−m . Pairing up complex exponentials with the exponents of opposite signs, and using de Moivre’s formula, we arrive at the real Fourier expansion that contains only cosine functions: x(t) = a a + 2 π 2 cos 2π t 2 2π 3t − cos ) + ··· . 2 (pure sine expansion of an odd rectangular waveform). Consider a periodic rectangular waveform of period P which is defined by the formula ⎧ ⎪ for 0 ≤ t < P4 ; ⎪a ⎪ ⎨ P 3P for 4 ≤ t < 4 ; x(t) = 0 ⎪ ⎪ ⎪ ⎩−a for 3P ≤ t < P .

So that P(X = xi ) = pi , i = 1, 2, . . , 0 < pi < 1, pi = 1. f. 6) i=1 where u(x) is the unit step function. f. has jumps of size pi at locations xi , and is constant at other points of the real line. , A ∩ B = ∅. 1 (Bernoulli distribution). In this case the values of X, that is the outcomes of the experiment, are assumed to be either 1 or 0 (think about it as a model of an experiment in which “success” or “failure” are the only possible outcomes), with P(X = 1) = p > 0, P(X = 0) = q > 0, with p, q satisfying condition p + q = 1.

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