This paper describes the time variant changes in satellite images using Self Organizing Feature Map (SOFM) technique associated with Artificial Neural Network. In this paper, we take a satellite image and find the time variant changes using above technique with the help of MATLAB. This paper reviews remotely sensed data analysis with neural networks. First, we present an overview of the main co...

| In this paper we exploit the one-to-one correspondences between the recursive least-squares (RLS) and Kalman variables to formulate extended forms of the RLS algorithm. Two particular forms of the extended RLS algorithm are considered, one pertaining to a system identiication problem and the other pertaining to the tracking of a chirped sinusoid in additive noise. For both of these applicatio...

Let T be a block lower triangular contraction, i.e., a contractive operator T = (ti,j) ∞ i,j=−∞ acting from a doubly infinite Hilbert space direct sum ⊕∞ j=−∞Kj into a doubly infinite Hilbert space direct sum ⊕∞ j=−∞ Lj . The operator ti,j , which maps Kj into Li, is the (i, j)-th entry in the operator matrix representation of T relative to the natural Hilbert space direct sum decompositions. I...

An algorithm for harmonic decomposition of time-variant signals is derived from a least squares harmonic (LSH) technique. The estimates of harmonic amplitudes and phases are formulated as the solution of a set of linear equations which minimizing mean square error; the signal frequency is modeled by a linear or quadratic polynomial and obtained via a local search over polynomial coefficients. A...

We introduce a variant of the cover time of a graph, called cover cost, in which the cost of a step is proportional to the number of yet uncovered vertices. It turns out that cover cost is more tractable than cover time; we provide an O(n) algorithm for its computation, as well as some explicit formulae. The two values are not very far from each other, and so cover cost might be a useful tool i...

The problem of global asymptotic stability of a time-variant mth-order difference equation is addressed. Stable regions in the parameter space will be derived for two cases: the case of a time-invariant parameter region, and the case of a time-variant parameter region. These results find applications in the area of adaptive digital filters.

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