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The aim of the report is to Demonstrate adaptive algorithms using Matlab. In this report a simulator was developed to the end user for simulating the results obtained from applications such as Noise canceller, Adaptive line enhancer, System Identification using adaptive algorithms (Least Mean Square, Normalized Least Mean Square, Leaky Least mean Squire algorithms, Recursive Least Square, Signed Least...
The present paper introduces a low complexity online convex analytic tool for time-varying sparse system identification and signal reconstruction tasks. The available information enters the design in two ways; (i) the sequentially arriving training data generate a sequence of simple closed convex sets, namely hyperslabs, and (ii) the information regarding the cardinality of the support of the unknown...
In this paper, a new variable step-size LMS algorithm based on computational verb rules is presented. This method allows the algorithm to converge faster and to produce smaller steady-state errors compared to other variable step-size LMS algorithms, even when the system is subjected to sudden changes. Furthermore, it provides a brand new framework that allows the designers to design adaptive algorithms...
This paper studies an affine combination of two NLMS adaptive filters, which is an interesting way of improving the performance of adaptive algorithms. The structure consists of two adaptive filters that adapt on the same input signal, one with a large and the other one with a small step size. Such a combination is capable of achieving fast initial convergence and small steady state error at the same...
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