基于MMSE和小波变换的语音增强算法

提出一种最小均方误差与小波变换相结合的改进算法来提高语音识别系统的性能. 首先通过小波变换对带噪语音进行多尺度分解, 然后对不同尺度的小波系数采用MMSE算法, 最后对MMSE处理过的小波系数进行重构得到增强语音. 实验结果表明: 与传统算法相比较, 提出的新算法去噪效果显著, 有效地提高了语音的质量.     

Early-warning signals for an outbreak of the influenza pandemic

Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CGR walk sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.     

Denoising via truncated sparse decomposition

This paper proposes a denoising algorithm called truncated sparse decomposition(TSD) algorithm,which combines the advantage of the sparse decomposition with that of the minimum energy model truncation operation.Experimental results on two real chaotic signals show that the TSD algorithm outperforms the recently reported denoising algorithms- non-negative sparse coding and singular value decomposition based method.     

信道补偿技术的发展及其在说话人识别上的应用

主要介绍了现阶段国内外有关信道补偿的主要技术方法、研究现状及未来发展方向,同时着重讨论了信道补偿技术在说话人识别上的应用。首先简述经验补偿和盲补偿两种方法以及它们的优缺点,然后分别讨论在特征空间、模型空间和得分空间上信道补偿技术在说话人识别上的应用。最后讨论了信道补偿技术在未来的发展方向。     

水泵吸水池内部流动非定常信号的小波分析

水泵吸水池内部的流动情况非常复杂,尤其是在吸入管的附近存在着很强的漩涡,这些漩涡使得流动的非定常特性非常强烈,本文用小波分析的方法来处理一种开敞式水泵吸水池内流动的非定常信号,它们分别是压力信号,振动信号和声音信号。在处理的过程中,应用离散小波变换,将不同时间和空间尺度下的信号进行分解,分别得到分解后的小波系数,再将不同层次的信号进行重构,并对各个层次的分解信号进行功率谱分析,得到这些非定常信号的分布规律。     

Fast algorithm of adaptive Fourier series

Adaptive Fourier decomposition (AFD, precisely 1‐D AFD or Core‐AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. The AFD merged with the greedy algorithm idea, and in particular, motivated the so‐called pre‐orthogonal greedy algorithm (pre‐OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD‐type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper constructs one novel method to perform the 1‐D AFD algorithm. We make use of the FFT algorithm to reduce the algorithm complexity, from the original to , where N denotes the number of the discretization points on the unit circle and M denotes the number of points in [0,1). This greatly enhances the applicability of AFD. Experiments are performed to show the high efficiency of the proposed algorithm.     

Novel Sampling and Reconstruction Method for Non-Bandlimited Impulse Signals

To sample non-bandlimited impulse signals, an extremely high-sampling rate analog-todigital converters (ADC) is required. Such an ADC is very difficult to be implemented with present semiconductor technology. In this paper, a novel sampling and reconstruction method for impulse signals is proposed. The required sampling rate of the proposed method is close to the signal innovation rate, which is much lower than the Nyquist rate in conventional Shannon sampling theory. Analysis and simulation results show that the proposed method can achieve very good reconstruction performance in the presence of noise.     

一种多卫星信号参数的快速盲估计方法

针对电子侦察领域中单通道多卫星信号处理这一新兴课题,提出了一种多信号盲多参数快速估计算法.该算法在检测到卫星信号的前提下,先进行信号个数的盲估计.在对目前存在的各种信号参数估计方法进行充分分析、研究的基础上,进而提出了一种通用的盲多参数快速估计方法,并对其中的滤波器群延迟等关键问题进行了深入分析.计算机仿真表明,与其它算法相比,该算法具有较好的多参数盲估计能力,且通用性和实时性强,能适应单通道多卫星信号的情况.     

基于SPCE061的语音提示交通灯控制系统的设计

使用凌阳科技的 SPCE061A 单片机以及模拟交通灯控制模组建立了带语音提示功能的十字路口智能交通灯控制系统,并在此平台上完成对交通灯状态进行模拟控制的软件设计.充分利用SPCE061A的语音特性,不仅具有红绿灯显示、倒计时功能,还能对红绿灯的转换进行语音提示,并能够根据路口需要设置红、绿灯的倒计时时长.     

Images-based suppression of unwanted global signals in resting-state functional connectivity studies

Correlated fluctuations of low-frequency fMRI signal have been suggested to reflect functional connectivity among the involved regions. However, large-scale correlations are especially prone to spurious global modulations induced by coherent physiological noise. Cardiac and respiratory rhythms are the most offending component, and a tailored preprocessing is needed in order to reduce their impact. Several approaches have been proposed in the literature, generally based on the use of physiological recordings acquired during the functional scans, or on the extraction of the relevant information directly from the images. In this paper, the performances of the denoising approach based on general linear fitting of global signals of noninterest extracted from the functional scans were assessed. Results suggested that this approach is sufficiently accurate for the preprocessing of functional connectivity data.