Non-uniform quantization for messages in Low-Density Parity-Check(LDPC)decoding canreduce implementation complexity and mitigate performance loss.But the distribution of messagesvaries in the iterative decoding.This l...Non-uniform quantization for messages in Low-Density Parity-Check(LDPC)decoding canreduce implementation complexity and mitigate performance loss.But the distribution of messagesvaries in the iterative decoding.This letter proposes a variable non-uniform quantized Belief Propaga-tion(BP)algorithm.The BP decoding is analyzed by density evolution with Gaussian approximation.Since the probability density of messages can be well approximated by Gaussian distribution,by theunbiased estimation of variance,the distribution of messages can be tracked during the iteration.Thusthe non-uniform quantization scheme can be optimized to minimize the distortion.Simulation resultsshow that the variable non-uniform quantization scheme can achieve better error rate performance andfaster decoding convergence than the conventional non-uniform quantization and uniform quantizationschemes.展开更多
An improved scalar Costa scheme (SCS) was proposed by using improved Watson perceptual model to adaptively decide quantization step size and scaling factor. The improved scheme equals to embed hiding data based on an ...An improved scalar Costa scheme (SCS) was proposed by using improved Watson perceptual model to adaptively decide quantization step size and scaling factor. The improved scheme equals to embed hiding data based on an actual image. In order to withstand amplitude scaling attack, the Watson perceptual model was redefined, and the improved scheme using the new definition can insure quantization step size in decoder that is proportional to amplitude scaling attack factor. The performance of the improved scheme outperforms that of SCS with fixed quantization step size. The improved scheme combines information theory and visual model.展开更多
According to the decline of recognition rate of speech recognition system in the noise environments, an improved perceptually non-uniform spectral compression feature extraction algorithm is put forward in this paper....According to the decline of recognition rate of speech recognition system in the noise environments, an improved perceptually non-uniform spectral compression feature extraction algorithm is put forward in this paper. This method can realize an effective compression of the speech signals and make the training and recognition environments more matching, so the recognition rate can be improved in the noise environments. By experimenting on the intelligent wheelchair platform, the result shows that the algorithm can effectively enhance the robustness of speech recognition, and ensure the recognition rate in the noise environments.展开更多
在传统的基于QIM(Quantization Index Modulation)嵌入的数字指纹系统中,由于量化步长固定,指纹系统的抗共谋性能和图像保真度较差。针对这些问题,提出一种抗共谋指纹方案,在嵌入指纹时添加随机信号到宿主信号的DCT域,根据Watson视觉模...在传统的基于QIM(Quantization Index Modulation)嵌入的数字指纹系统中,由于量化步长固定,指纹系统的抗共谋性能和图像保真度较差。针对这些问题,提出一种抗共谋指纹方案,在嵌入指纹时添加随机信号到宿主信号的DCT域,根据Watson视觉模型选择量化步长。实验结果表明,与原始的QIM指纹方案相比,采用提出方案的QIM指纹系统在抗共谋能力和视觉失真度方面都具有较好的性能。展开更多
A new three-dimensional(3D) audio coding approach is presented to improve the spatial perceptual quality of 3D audio. Different from other audio coding approaches, the distance side information is also quantified, and...A new three-dimensional(3D) audio coding approach is presented to improve the spatial perceptual quality of 3D audio. Different from other audio coding approaches, the distance side information is also quantified, and the non-uniform perceptual quantization is proposed based on the spatial perception features of the human auditory system, which is named as concentric spheres spatial quantization(CSSQ) method. Comparison results were presented, which showed that a better distance perceptual quality of 3D audio can be enhanced by 5.7%~8.8% through extracting and coding the distance side information comparing with the directional audio coding, and the bit rate of our coding method is decreased of 8.07% comparing with the spatial squeeze surround audio coding.展开更多
基金the Aerospace Technology Support Foun-dation of China(No.J04-2005040).
文摘Non-uniform quantization for messages in Low-Density Parity-Check(LDPC)decoding canreduce implementation complexity and mitigate performance loss.But the distribution of messagesvaries in the iterative decoding.This letter proposes a variable non-uniform quantized Belief Propaga-tion(BP)algorithm.The BP decoding is analyzed by density evolution with Gaussian approximation.Since the probability density of messages can be well approximated by Gaussian distribution,by theunbiased estimation of variance,the distribution of messages can be tracked during the iteration.Thusthe non-uniform quantization scheme can be optimized to minimize the distortion.Simulation resultsshow that the variable non-uniform quantization scheme can achieve better error rate performance andfaster decoding convergence than the conventional non-uniform quantization and uniform quantizationschemes.
基金The National Basic Research Program (973) of China (No. 2005CB321804)
文摘An improved scalar Costa scheme (SCS) was proposed by using improved Watson perceptual model to adaptively decide quantization step size and scaling factor. The improved scheme equals to embed hiding data based on an actual image. In order to withstand amplitude scaling attack, the Watson perceptual model was redefined, and the improved scheme using the new definition can insure quantization step size in decoder that is proportional to amplitude scaling attack factor. The performance of the improved scheme outperforms that of SCS with fixed quantization step size. The improved scheme combines information theory and visual model.
基金supported by the International Science and Technology Cooperation Program of China (2010DFA12160)the National Natural Science Foundation of China (51075420),the National Natural Science Foundation of China (60905066)the Science & Technology Research Project of Chongqing CSTC(2010AA2055)
文摘According to the decline of recognition rate of speech recognition system in the noise environments, an improved perceptually non-uniform spectral compression feature extraction algorithm is put forward in this paper. This method can realize an effective compression of the speech signals and make the training and recognition environments more matching, so the recognition rate can be improved in the noise environments. By experimenting on the intelligent wheelchair platform, the result shows that the algorithm can effectively enhance the robustness of speech recognition, and ensure the recognition rate in the noise environments.
文摘在传统的基于QIM(Quantization Index Modulation)嵌入的数字指纹系统中,由于量化步长固定,指纹系统的抗共谋性能和图像保真度较差。针对这些问题,提出一种抗共谋指纹方案,在嵌入指纹时添加随机信号到宿主信号的DCT域,根据Watson视觉模型选择量化步长。实验结果表明,与原始的QIM指纹方案相比,采用提出方案的QIM指纹系统在抗共谋能力和视觉失真度方面都具有较好的性能。
基金supported by National High Technology Research and Development Program of China (863 Program, No. 2015AA016306)National Nature Science Foundation of China (No. 61662010, 61231015, 61471271, 61761044, 61762005)
文摘A new three-dimensional(3D) audio coding approach is presented to improve the spatial perceptual quality of 3D audio. Different from other audio coding approaches, the distance side information is also quantified, and the non-uniform perceptual quantization is proposed based on the spatial perception features of the human auditory system, which is named as concentric spheres spatial quantization(CSSQ) method. Comparison results were presented, which showed that a better distance perceptual quality of 3D audio can be enhanced by 5.7%~8.8% through extracting and coding the distance side information comparing with the directional audio coding, and the bit rate of our coding method is decreased of 8.07% comparing with the spatial squeeze surround audio coding.
