Download e-book for iPad: An Introduction to Statistical Signal Processing by Gray R.M., Davisson L.D.

By Gray R.M., Davisson L.D.

This quantity describes the basic instruments and methods of statistical sign processing. At each level, theoretical rules are associated with particular functions in communications and sign processing. The publication starts off with an summary of uncomplicated chance, random items, expectation, and second-order second concept, via a wide selection of examples of the preferred random procedure versions and their uncomplicated makes use of and homes. particular purposes to the research of random indications and structures for speaking, estimating, detecting, modulating, and different processing of signs are interspersed in the course of the textual content.

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If the two numbers a and b are suitably chosen then xn should appear to be uniform. ) In fact, since there are only a finite number (albeit large) of possible numbers that can be represented on a digital computer, this algorithm must eventually repeat and hence xn must be a periodic sequence. The goal of designing a good pseudo-random number generater is to make the period as long as possible and to make the sequences produced look as much as possible like a random sequence in the sense that statistical tests for independence are fooled.

The first is that probabilities must satisfy some consistency properties, we cannot arbitrarily define probabilities of distinct subsets of [0, 1) (or, more generally, ) without regards to the implications of probabilities for other sets; the probabilities must be consistent with each other in the sense that they do not contradict each other. 2. SPINNING POINTERS AND FLIPPING COINS 17 computing the probability of an interval, then both formulas must give the same numerical result — as they do in this example.

2(b). For example, the sequences of sets [1, 1 + 1/n) and (1−1/n, 1+1/n) are decreasing. Again we have a natural notion of the limit of this sequence: Both these sequences of sets collapse to the point of singleton set {1} — the point in common to all the sets. This suggests a formal definition based on the countably infinite intersection of the sets. Given a decreasing sequence of sets Fn ; n = 1, 2, . . , we define the limit of the sequence by ∞ lim Fn = n→∞ Fn , n=1 34 CHAPTER 2. PROBABILITY that is, a point is in the limit of a decreasing sequence of sets if and only if it is contained in all the sets of the sequence.

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An Introduction to Statistical Signal Processing by Gray R.M., Davisson L.D.


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