Sampling Moments and Reconstructing Signals

Consider the problem of sampling signals which are not bandlimited, but still have a finite number of degrees of freedom per unit of time, such as, for example, piecewise polynomial or piecewise sinusoidal signals, and call the number of degrees of freedom per unit of time the rate of innovation. Classical sampling theory does not enable a perfect reconstruction of such signals since the band is not limited.

Recently, it was shown that by using an adeq ....etc

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Abstract
The problem of estimating the kth frequency moment Fk over a data stream by looking at the items exactly once as they arrive was posed in . A succession of algorithms have been proposed for this problem . Recently, Indyk and Woodru® have presented the ¯rst algorithm for estimating Fk, for k > 2, using space ~O (n1¡2=k), matching the space lower bound (up to poly-logarithmic factors) for this problem (n is the number of distinct items occurring in the stream.) In this paper, we pre ....etc

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image reconstruction using krawtchouk moments ....etc

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Abstract.
We consider the problem of estimating hybrid frequency moments of two dimensional data
streams. In this model, data is viewed to be organized in a matrix form (Ai;j)1i;j;n. The entries
Ai;j are updated coordinate-wise, in arbitrary order and possibly multiple times. The updates include
both increments and decrements to the current value of Ai;j . The hybrid frequency moment Fp;q(A)
is dened as
Pn
j=1
....etc

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Abstract.
Space-economical estimation of the pth frequency moments, defined as Fp = Pn i=1|fi|p, for p > 0, are of interest in estimating all-pairs distances in a large data matrix , machine learning, and in data stream computation. Random sketches formed by the inner product of the frequency vector f1, . . . , fn with a suitably chosen random vector were pioneered by Alon, Matias and Szegedy , and have since played a central role in estimating Fp and for data stream computations in general. The concept of p-stable sketches for ....etc

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I'm working on image analysis using krawtchouk moments.
I am in need of help inorder to write matlab codings for the krawtchouk moments for an image.
How to write codings for this moments ??
please put your replies forward.... ....etc

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I need the MATLAb code of Krawtchouk Moments for Image Processing research purpose ....etc

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Abstract.
The problem of estimating the kth frequency moment Fk, for any
non-negative integral value of k, over a data stream by looking at the items exactly
once as they arrive, was considered in a seminal paper by Alon, Matias and
Szegedy . They present a sampling based algorithm to estimate Fk where,
k  2, using space ˜O(n1−1/k)). Coppersmith and Kumar and , using
different methods, present algorithms for estimating Fk with space complexity
˜O
(n1−1/(k−1)). In this paper, we present an algorithm for es ....etc

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Moments and Channel Capacity of Single and
Dual-Branch Receivers Over Weibull Fading Channels



ABSTRACT

Diversity combining receivers is the well-known technique used to combat fad-
ing and improve system performance. There are several diversity reception methods
employed in digital communication receivers including maximal-ratio combining, se-
lection combining and switched diversity. Among the combining methods, switched
diversity offers one of the least complexity solution for fading mitigation and ....etc

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Summary
This paper proposes a new approach investigating the applicationof moment method to evaluate a set of candidate features and toselect an informative subset to be used as input data for a neuralnetwork classifier. The first step (pre-processing) of proposedmethod takes into account the discriminative properties ofinvariant krawtchouk moments. The second step (recognition) isachieved by using multilayer feedforward neural network(MFNN) as a classifier with the stochastic back propagation as alearning algorithm. Finite vectors obt ....etc

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