IEEE Transactions on Information Theory

Volume 16 Issue 2 • March 1970

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Displaying Results 1 - 25 of 26
  • Information rates of Wiener processes

    Publication Year: 1970, Page(s):134 - 139
    Cited by:  Papers (36)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (786 KB)

    Rate distortion functions are calculated for time discrete and time continuous Wiener processes with respect to the mean squared error criterion. In the time discrete case, we find the interesting result that, for0 leq D leq sigma^2 /4,R(D)for the Wiener process is identical toR(D)for the sequence of zero mean independent normally distributed increments of variance... View full abstract»

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  • On the representation of continuous parameter processes by a sequence of random variables

    Publication Year: 1970, Page(s):139 - 141
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (435 KB)

    This paper examines the question of representing a continuous parameter random process{ x_t, t in T }by a sequence of random variables "without loss of information." The principal result is that such a representation by expansion coefficients relative to a basis{ phi_i }ofmathcal{L}_2(T)is always possible, regardless of the orthogonality of{ phi_i }and o... View full abstract»

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  • Alias-free randomly timed sampling of stochastic processes

    Publication Year: 1970, Page(s):147 - 152
    Cited by:  Papers (64)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1058 KB)

    The notion of alias-free sampling is generalized to apply to random processesx(t)sampled at random timest_n; sampling is said to be alias free relative to a family of spectra if any spectrum of the family can be recovered by a linear operation on the correlation sequence{r(n)}, wherer(n) = E[x(l_{m+n}) overline{x(t_m)}]. The actual sampling timest_n... View full abstract»

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  • Bounds on performance of optimum quantizers

    Publication Year: 1970, Page(s):172 - 184
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1620 KB)

    A quantizerQdivides the range [0, 1] of a random variablexintoKquantizing intervals theith such interval having lengthDelta x_i. We define the quantization error for a particular value ofx(unusually) as the length of the quantizing interval in whichxfinds itself, and measure quantizer performance (unusually) by ther<... View full abstract»