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Stable continuous-wave single-frequency intracavity frequency-doubled laser with intensity noise suppressed in audio frequency region

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Chinese Physics B 2019年第9期28卷 197-202页

作者： Ying-Hao Gao Yuan-Ji Li Jin-Xia Feng Kuan-Shou Zhang State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China

We demonstrated a continuous wave(cw) single-frequency intracavity frequency-doubled Nd:YVO_4/LBO laser with 532 nm output of 7.5 W and 1.06 μm output of 3.1 W, and low intensity noise in audio frequency *** suppress the intensity noise of the high power 532 nm laser, a laser frequency locking system and a feedback loop based on a Mach-Zehnder interferometer were designed and *** influences of the frequency stabilization and the crucial parameters of the MZI, such as the power splitting ratio of the beam splitters and the locking state of the MZI, on the intensity noise of the 532 nm laser were investigated in *** the experimental optimizations, the laser intensity noise in the frequency region from 0.4 kHz to 10 kHz was significantly suppressed.

关键词： continuous wave single-frequency intracavity frequency-doubled laser noise suppression power stabilization audio frequency

A post-processing method for true random number generators based on hyperchaos with applications in audio-based generators

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Frontiers of Computer Science 2020年第6期14卷 85-95页

作者： Je Sen TEH Weijian TENG Azman SAMSUDIN Jiageng CHEN School of Computer Sciences Universiti Sains MalaysiaPenang 11800Malaysia School of Engineering and Technology INTI International College PenangPenang 11900Malaysia School of Computer Central China Normal UniversityWuhan 430079China

True random number generators(TRNG)are important counterparts to pseudorandom number generators(PRNG).especially for high security applications such as *** produce unpredictable,non-repeatablerandom ***,most TRNGs require specialized hardware to extract entropy from physical phenomena and tend to be slower than *** generators usually require post-processing algorithms to eliminate biases but in *** *** this paper.a newpost-processing method based on hyperchaos is proposed forsoftware-based TRNGs which not only eliminates statisticalbiases but also provides amplification in order to improve the performance of *** proposed method utilizes the inherent characteristics of chaos such as hypersensitivity to input shanugeri,diffusisn,and csnfusion sapabilities to ushievethese *** bits of a physical entropy source areused to perturb the parameters of a hyperchaotic map,which is then iterated to produce a set of random output *** de-pict the feasibility of the proposed post-processing *** is applied in designing TRNGs based on digital *** are analyzed to identify statistical defects in addition to forward and backward *** indicate that the proposed generators are able to produce secure true random sequences at a high throughput,which in turn reflects on the effectiveness of the proposed post-processing method.

关键词： audio chaos theory chaotic map entropy hyperchaos post-processing random number generator security

Experimental Investigation of Low Pressure audio Frequency Discharge in Argon

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Chinese Physics Letters 2012年第10期29卷 144-147页

作者： A.A.Azooz A.Y.Owaid Department of Physics College of ScienceMosul UniversityMosul Iraq Technical Institute of Mosul MosulIraq

Experimental data obtained on audio frequency(100–10000 Hz)discharge in argon at four pressures 50,60,70,and 80 mTorr are *** data show significant changes of the discharge current waveform with *** changes seem to be associated with the glow discharge profile and *** empirical model based on the assumption of a frequency-dependent breakdown voltage is used to describe the experimental data.

关键词： breakdown audio frequency

Tensor Completion for Recovering Multichannel audio Signal with Missing Data

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China Communications 2019年第4期16卷 186-195页

作者： Lidong Yang Min Liu Jing Wang Xiang Xie Jingming Kuang School of Information Science and Technology Beijing Institute of Technology School of Information Engineering Inner Mongolia University of Science and Technology

The quality of a multichannel audio signal may be reduced by missing data, which must be recovered before use. The data sets of multichannel audio can be quite large and have more than two axes of variation, such as channel, frame, and feature. To recover missing audio data, we propose a low-rank tensor completion method that is a high-order generalization of matrix completion. First, a multichannel audio signal with missing data is modeled by a three-order tensor. Next, tensor completion is formulated as a convex optimization problem by defining the trace norm of the tensor, and then an augmented Lagrange multiplier method is used for solving the constrained optimization problem. Finally, the missing data is replaced by alternating iteration with a tensor computation. Experiments were conducted to evaluate the effectiveness on data of a 5.1-channel audio signal. The results show that the proposed method outperforms state-of-the-art methods. Moreover, subjective listening tests with MUSHRA(Multiple Stimuli with Hidden Reference and Anchor) indicate that better audio effects were obtained by tensor completion.

关键词： tensor completion missing data multichannel audio convex optimization

A Novel Two-Layer Model for Overall Quality Assessment of Multichannel audio

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China Communications 2017年第9期14卷 42-51页

作者： Jiyue Liu Jing Wang Min Liu Xiang Xie Jingming Kuang School of Information and Technology Beijing Institute of Technology

With the development of multichannel audio systems, corresponding audio quality assessment techniques, especially the objective prediction models, have received increasing attention. Existing methods, such as PEAQ(Perceptual Evaluation of audio Quality) recommended by ITU, usually lead to poor results when assessing multichannel audio, which have little correlation with subjective scores. In this paper, a novel two-layer model based on Multiple Linear Regression(MLR) and Neural Network(NN) is proposed. Through the first layer, two indicators of multichannel audio, audio Quality Score(AQS) and Spatial Perception Score(SPS) are derived, and through the second layer the overall score is output. The final results show that this model can not only improve the correlation with the subjective test score by 30.7% and decrease the Root Mean Square Error(RMSE) by 44.6%, but also add two new indicators: AQS and SPS, which can help reflect the multichannel audio quality more clearly.

关键词： multichannel audio two-layermodel audio quality assessment multiple lin-ear regression neural network

Nonlinear Prediction with Deep Recurrent Neural Networks for Non-Blind audio Bandwidth Extension

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China Communications 2018年第4期15卷 72-85页

作者： Lin Jiang Ruimin Hu Xiaochen Wang Weiping Tu Maosheng Zhang National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan 430072 China Institute of Big Data and internet Innovation Hunan University of Commerce Changsha 410205 China Software College East China University of Technology Nanchang 330013 China Collaborative Innovation Center for Economics crime investigation and prevention technology Jiangxi Province Nanchang 330103China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan 430072 China Collaborative Innovation Center of Geospatial Technology Wuhan 430079 China

Non-blind audio bandwidth extension is a standard technique within contemporary audio codecs to efficiently code audio signals at low bitrates. In existing methods, in most cases high frequencies signal is usually generated by a duplication of the corresponding low frequencies and some parameters of high frequencies. However, the perception quality of coding will significantly degrade if the correlation between high frequencies and low frequencies becomes weak. In this paper, we quantitatively analyse the correlation via computing mutual information value. The analysis results show the correlation also exists in low frequency signal of the context dependent frames besides the current frame. In order to improve the perception quality of coding, we propose a novel method of high frequency coarse spectrum generation to improve the conventional replication method. In the proposed method, the coarse high frequency spectrums are generated by a nonlinear mapping model using deep recurrent neural network. The experiments confirm that the proposed method shows better performance than the reference methods.

关键词： audio coding non-blind audiobandwidth extension context correlation deeprecurrent neural network

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High Quality audio Object Coding Framework Based on Non-Negative Matrix Factorization

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China Communications 2017年第9期14卷 32-41页

作者： Tingzhao Wu Ruimin Hu Xiaochen Wang Shanfa Ke Jinshan Wang National Engineering Research Center for Multimedia Software School of Computer ScienceWuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Collaborative Innovation Center of Geospatial Technology

Object-based audio coding is the main technique of audio scene coding. It can effectively reconstruct each object trajectory, besides provide sufficient flexibility for personalized audio scene reconstruction. So more and more attentions have been paid to the object-based audio coding. However, existing object-based techniques have poor sound quality because of low parameter frequency domain resolution. In order to achieve high quality audio object coding, we propose a new coding framework with introducing the non-negative matrix factorization(NMF) method. We extract object parameters with high resolution to improve sound quality, and apply NMF method to parameter coding to reduce the high bitrate caused by high resolution. And the experimental results have shown that the proposed framework can improve the coding quality by 25%, so it can provide a better solution to encode audio scene in a more flexible and higher quality way.

关键词： object-based audio coding non-negative matrix factorization audio scenecoding

Initialization for NMF-Based audio Source Separation Using Priors on Encoding Vectors

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China Communications 2019年第9期16卷 177-186页

作者： Jaeuk Byun Jong Won Shin Electrical Engineering and Computer Science Gwangju Institute of Science and Technology (GIST)

Nonnegative matrix factorization(NMF)has shown good performances on blind audio source separation(BASS).While the NMF analysis is a non-convex optimization problem when both the basis and encoding matrices need to be estimated simultaneously,the source separation step of the NMF-based BASS with a fixed basis matrix has been considered ***,because the basis matrix for the BASS is typically constructed by concatenating the basis matrices trained with individual source signals,the subspace spanned by the basis vectors for one source may overlap with that for other *** this paper,we have shown that the resulting encoding vector is not unique when the subspaces spanned by basis vectors for the sources overlap,which implies that the initialization of the encoding vector in the source separation stage is not ***,we propose a novel method to initialize the encoding vector for the separation step based on the prior model of the encoding *** results showed that the proposed method outperformed the uniform random initialization by 1.09 and 2.21dB in the source-to-distortion ratio,and 0.20 and 0.23 in PESQ scores for supervised and semi-supervised cases,respectively.

关键词： blind audio source separation nonnegative matrix factorization speech enhancement

audio Sensors Fusion Based on Vote for Robot Navigation

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Audio Sensors Fusion Based on Vote for Robot Navigation