فهرس المقالات Impulsive Noise

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  1 - BER Performance Analysis of MIMO-OFDM Communication Systems Using Iterative Technique Over Indoor Power Line Channels in an Impulsive Noise Environment
  Mohammad Reza Ahadiat Paeez Azmi Afrooz Haghbin
  10.7508/jist.2016.01.005
  This paper addresses the performance of MIMO-OFDM communication system in environments where the interfering noise exhibits non-Gaussian behavior due to impulsive phenomena. It presents the design and simulation of an iterative technique that aims to minimize the effect أکثر

  This paper addresses the performance of MIMO-OFDM communication system in environments where the interfering noise exhibits non-Gaussian behavior due to impulsive phenomena. It presents the design and simulation of an iterative technique that aims to minimize the effect of impulsive noise on the performance of the MIMO-OFDM communication system under Additive White Gaussian Noise (AWGN) channel. This is a new method to recover the signals corrupted by impulsive noise in MIMO-OFDM systems over In-home Power Line Channel. The location and amplitude Impulsive noise at the receiver using an adaptive threshold to be determined. Reduced Impulsive noise effects using the mask based on the soft decision method. By iteration, the original signal estimation can be used to improve the impulsive noise estimation. This continuous loop impulsive noise detection and mitigation a better estimate of the original signal is obtained. The Bit Error Rate (BER) performance of the MIMO-OFDM system in an impulsive noise environment was evaluated. The results show the superiority and robustness of the proposed method. تفاصيل المقالة
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  2 - Acoustic Noise Cancellation Using an Adaptive Algorithm Based on Correntropy Criterion and Zero Norm Regularization
  Mojtaba Hajiabadi
  10.7508/jist.2015.03.003
  The least mean square (LMS) adaptive algorithm is widely used in acoustic noise cancellation (ANC) scenario. In a noise cancellation scenario, speech signals usually have high amplitude and sudden variations that are modeled by impulsive noises. When the additive noise أکثر

  The least mean square (LMS) adaptive algorithm is widely used in acoustic noise cancellation (ANC) scenario. In a noise cancellation scenario, speech signals usually have high amplitude and sudden variations that are modeled by impulsive noises. When the additive noise process is nonGaussian or impulsive, LMS algorithm has a very poor performance. On the other hand, it is well-known that the acoustic channels usually have sparse impulse responses. When the impulse response of system changes from a non-sparse to a highly sparse one, conventional algorithms like the LMS based adaptive filters can not make use of the priori knowledge of system sparsity and thus, fail to improve their performance both in terms of transient and steady state. Impulsive noise and sparsity are two important features in the ANC scenario that have paid special attention, recently. Due to the poor performance of the LMS algorithm in the presence of impulsive noise and sparse systems, this paper presents a novel adaptive algorithm that can overcomes these two features. In order to eliminate impulsive disturbances from speech signal, the information theoretic criterion, that is named correntropy, is used in the proposed cost function and the zero norm is also employed to deal with the sparsity feature of the acoustic channel impulse response. Simulation results indicate the superiority of the proposed algorithm in presence of impulsive noise along with sparse acoustic channel. تفاصيل المقالة