Adaptive IIR filtering

Shynk, J.J.

doi:10.1109/53.29644

Cited by 513 publications

(232 citation statements)

References 39 publications

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“…This is what adaptation means. Moreover there is a need to have a set of steps or certain procedure called algorith m by which this process of adaptation is carried out [6]. adaptive algorithm, which adjusts the variable filter to satisfy some predetermined ru les.…”

Section: Adaptive Signal Processingmentioning

confidence: 99%

Interference Cancellation in Aircraft Cockpit by Adaptive Filters

Arun¹

2016

MATEC Web of Conferences

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Abstract. T his paper investigates on the development and implementation of adaptive noise cancellation (ANC) algorithm meant for mitigating the high level engine noise in the cockpit of an aircraft, which makes the speech signal unintelligible. Adaptive filters configured as interference canceller have the potential application in mitigat ing the above interference. A comparative study of Gradient based adaptive Infinite Impulse Response (IIR) algorithm and its modified version is performed using MAT LAB sim ulator in terms of converging speed. From the simulation result the best IIR algorithm is used for implementation in Performance Optimized with Enhanced RISC PC (Power PC) 7448.

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Section: Adaptive Signal Processingmentioning

confidence: 99%

Interference Cancellation in Aircraft Cockpit by Adaptive Filters

Arun¹

2016

MATEC Web of Conferences

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“…When the system input is white and the noise is absent, the MSE cost function has a global minimum at u global = [−0.311 − 0.906] T with the value of the normalised MSE 0.2772 and a local minimum at u local = [0.114 0.519] T with the normalised MSE value 0.9762 [11]. In the population initialisation, the parameters were uniformly randomly chosen as (a 0 , b 1 ) ∈ (−1.0, 1.0)× (−0.999, 0.999).…”

Section: Optimisation Applicationsmentioning

confidence: 99%

A Search Algorithm for Global Optimisation

Chen

Wang

Harris

2005

Lecture Notes in Computer Science

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Abstract. This paper investigates a global search optimisation technique, referred to as the repeated weighted boosting search. The proposed optimisation algorithm is extremely simple and easy to implement. Heuristic explanation is given for the global search capability of this technique. Comparison is made with the two better known and widely used global search techniques, known as the genetic algorithm and adaptive simulated annealing. The effectiveness of the proposed algorithm as a global optimiser is investigated through several examples.

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“…Adaptive IIR filters suffer from two important drawbacks, namely potential instability problems and the presence of local minima in the error function [18]. Even when the stability conditions are easily met, such as in the case of lattice or biquads, the computational complexity is higher than for FIR adaptive filters.…”

Section: Case Of Iir Synapsesmentioning

confidence: 99%