By Wojbor A. Woyczynski

ISBN-10: 0817643982

ISBN-13: 9780817643980

ISBN-10: 0817645160

ISBN-13: 9780817645168

This article serves as a very good advent to stats for sign research. remember that it emphasizes idea over numerical tools - and that it truly is dense. If one isn't really trying to find long motives yet in its place desires to get to the purpose speedy this e-book will be for them.

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Additional resources for A First Course in Statistics for Signal Analysis

Example text

1. The period P = 1 and the amplitude a = 1. Calculation of coefficients zm in the expansion of the signal x(t) into a complex Fourier series is here straightforward: For m = 0, z0 = P 1 P 0 x(t)e−j2π 0t/P dt = a P 3P P −0+P − 4 4 = a . 1 Complex Fourier series for periodic signals 23 a −j(2π /2)m ej(π /2)m − e−j(π /2)m e πm 2j π π a a cos π m sin m = − (−1)m sin m. =− πm 2 πm 2 =− π If m = 2k, then sin 2 m = 0, and if m = 2k + 1, k = 0, ±1, ±2, . . , then π sin 2 m = (−1)k , which gives, for k = ±1, ±2, .

2. The histogram of daily voltage readings on an electrical outlet. 2. In this chapter, we will discuss analytical tools for the study of such random quantities. The discrete and continuous random quantities are introduced, but we also show that, in the presence of fractal phenomena, the above classification is not exhaustive. , will symbolize measurements of experiments with uncertain outcomes. 1 Discrete, continuous, and singular random quantities 49 PX (a, b] = P(a < X ≤ b) = P(X ∈ (a, b]) that X takes values in the interval (a, b].

Approximation of the Dirac delta δ(f ) by two-sided exponential |f | 1 1 1 functions ( 2a ) exp(− a ) for a = 1, 3 , and 9 . 2) integrating a function against the Dirac delta produces a value of the function at f = 0. 2), which can actually be taken as a formal definition of the Dirac delta. 1): Indeed, if function X(f ) is regular enough, then ∞ −∞ δ(f )X(f )df = lim →0 = lim →0 ∞ −∞ 1 2 r (f )X(f )df − X(f )df = X(0) in view of the fundamental theorem of calculus. 5) The last property is often intuitively stated as δ(f ) = 0 for f ≠ 0.

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

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