EEG/ERP Adaptive Noise Canceller Design with Controlled Search Space (CSS) Approach in Cuckoo and Other Optimization Algorithms

In this paper, a system for filtering event-related potentials/electroencephalograph is exhibited by adaptive noise canceller through an optimization algorithm, oppositional hybrid whale-grey wolf optimization algorithm (OWGWA). The OWGWA can choose the control parameters of the grey wolf algorithm utilizing whale parameters. To balance out the randomness of optimization strategies another methodology is implemented called controlled search space. Adaptive filter's noise reduction capability has been tested through adding adaptive white Gaussian noise over contaminated EEG signals at different noise levels. The performance of the proposed OWGWA-CSS algorithm is evaluated by signal to noise ratio in dB, mean value, and the relationship between resultant and input ERP. In this work, ANCs are also implemented by utilizing other optimization techniques. In average cases of noisy environment, comparative analysis shows that the proposed OWGWA-CSS technique provides higher SNR value, significantly lower mean and higher correlation as compared to other techniques.

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Car Noise Suppression Using Adaptive Noise Canceller with Speech Suppressors

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.136.1218 ◽

2016 ◽

Vol 136 (8) ◽

pp. 1218-1229

Author(s):

Yuya Honda ◽

Arata Kawamura ◽

Youji Iiguni

Keyword(s):

Noise Suppression ◽

Adaptive Noise ◽

Adaptive Noise Canceller

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Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194017500127 ◽

2017 ◽

Vol 27 (03) ◽

pp. 343-372 ◽

Cited By ~ 10

Author(s):

Umit Can ◽

Bilal Alatas

Keyword(s):

Association Rules ◽

Optimization Problems ◽

Search Algorithm ◽

Fitness Function ◽

Optimization Algorithms ◽

Gravitational Search Algorithm ◽

Search Space ◽

Search Method ◽

Quantitative Association Rules ◽

Gravitational Search

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.

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A Robust Dual-Microphone Generalized Sidelobe Canceller Using a Bone-Conduction Sensor for Speech Enhancement

Sensors ◽

10.3390/s21051878 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1878

Author(s):

Yi Zhou ◽

Haiping Wang ◽

Yijing Chu ◽

Hongqing Liu

Keyword(s):

Speech Enhancement ◽

Speech Intelligibility ◽

Bone Conduction ◽

Speech Quality ◽

Generalized Sidelobe Canceller ◽

Spatially Distributed ◽

Interference Signals ◽

Adaptive Noise ◽

Adaptive Noise Canceller ◽

Sidelobe Canceller

The use of multiple spatially distributed microphones allows performing spatial filtering along with conventional temporal filtering, which can better reject the interference signals, leading to an overall improvement of the speech quality. In this paper, we propose a novel dual-microphone generalized sidelobe canceller (GSC) algorithm assisted by a bone-conduction (BC) sensor for speech enhancement, which is named BC-assisted GSC (BCA-GSC) algorithm. The BC sensor is relatively insensitive to the ambient noise compared to the conventional air-conduction (AC) microphone. Hence, BC speech can be analyzed to generate very accurate voice activity detection (VAD), even in a high noise environment. The proposed algorithm incorporates the VAD information obtained by the BC speech into the adaptive blocking matrix (ABM) and adaptive noise canceller (ANC) in GSC. By using VAD to control ABM and combining VAD with signal-to-interference ratio (SIR) to control ANC, the proposed method could suppress interferences and improve the overall performance of GSC significantly. It is verified by experiments that the proposed GSC system not only improves speech quality remarkably but also boosts speech intelligibility.

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Dual-Mic Speech Enhancement Based on TF-GSC with Leakage Suppression and Signal Recovery

Applied Sciences ◽

10.3390/app11062816 ◽

2021 ◽

Vol 11 (6) ◽

pp. 2816

Author(s):

Hansol Kim ◽

Jong Won Shin

Keyword(s):

Speech Enhancement ◽

Wiener Filter ◽

Signal Recovery ◽

Gain Function ◽

Microphone Signal ◽

Perceptual Evaluation ◽

Blocking Matrix ◽

Adaptive Noise ◽

Adaptive Noise Canceller ◽

Sidelobe Canceller

The transfer function-generalized sidelobe canceller (TF-GSC) is one of the most popular structures for the adaptive beamformer used in multi-channel speech enhancement. Although the TF-GSC has shown decent performance, a certain amount of steering error is inevitable, which causes leakage of speech components through the blocking matrix (BM) and distortion in the fixed beamformer (FBF) output. In this paper, we propose to suppress the leaked signal in the output of the BM and restore the desired signal in the FBF output of the TF-GSC. To reduce the risk of attenuating speech in the adaptive noise canceller (ANC), the speech component in the output of the BM is suppressed by applying a gain function similar to the square-root Wiener filter, assuming that a certain portion of the desired speech should be leaked into the BM output. Additionally, we propose to restore the attenuated desired signal in the FBF output by adding some of the microphone signal components back, depending on how microphone signals are related to the FBF and BM outputs. The experimental results showed that the proposed TF-GSC outperformed conventional TF-GSC in terms of the perceptual evaluation of speech quality (PESQ) scores under various noise conditions and the direction of arrivals for the desired and interfering sources.

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