Essay about A Proposed ICA Algorithm

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Proposed ICA algorithm
This algorithm performs adaptive optimization of kurtosis based contrast function in floating point arithmetic. The main aim of this algorithm development is to reduce the number of manipulations and to improve the performance of ICA algorithm in terms of convergence speed, area, frequency and power. The convergence speed of the algorithm is improved by focusing the search in particular directions rather than searching for the solution in a random manner. The random number generator unit present in FastICA has been replaced by an adaptive optimization unit .This adaptive optimization unit updates the weight values based on the kurtosis function. Since adaptive optimization unit contains a subtractor and
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Proposed ICA algorithm
This algorithm performs adaptive optimization of kurtosis based contrast function in floating point arithmetic. The main aim of this algorithm development is to reduce the number of manipulations and to improve the performance of ICA algorithm in terms of convergence speed, area, frequency and power. The convergence speed of the algorithm is improved by focusing the search in particular directions rather than searching for the solution in a random manner. The random number generator unit present in FastICA has been replaced by an adaptive optimization unit .This adaptive optimization unit updates the weight values based on the kurtosis function. Since adaptive optimization unit contains a subtractor and comparator, it involves lesser area and power when compared to random generator unit. In this algorithm, initial weight vectors for estimating the demixing matrix B in (2), are assumed as Wi’s. This algorithm computes new weights from the initial weights in adaptive manner based on absolute value of fitness function. Contrast function Iteration Unit
The efficiency of source estimation is based on the selection of cost functions, also called as objective functions or contrast functions. The Cost function is a measure of independence [4]. Some measures of independence are Kurtosis, mutual information and negentropy. Although different contrast functions exist, the most popular contrast function used in ICA is kurtosis. Central limit
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