Analog VLSI Circuits for Competitive Learning Networks

An investigation is made concerning implementations of competitive learning algorithms in analog VLSI circuits and systems. Analog and low power digital circuits for competitive learning are currently important for their applications in computationally-efficient speech and image compression by vector quantization, as required for example in portable multi-media terminals. A summary of competitive learning models is presented to indicate the type of VLSI computations required, and the effects of weight quantization are discussed. Analog circuit representations of computational primitives for learning and evaluation of distortion metrics are discussed. The present state of VLSI implementations of hard and soft competitive learning algorithms are described, as well as those for topological feature maps. Tolerance of learning algorithms to observed analog circuit properties is reported. New results are also presented from simulations of frequency-sensitive and soft competitive learning concerning sensitivity of these algorithms to precision in VLSI learning computations. Applications of these learning algorithms to unsupervised feature extraction and to vector quantization of speech and images are also described.     

Quantized based image watermarking in an independent domain

This paper presents a performance study for two well known quantized based watermarking schemes Scalar Costa Scheme (SCS), and Trellis Coded Quantization scheme (TCQ) in an independent domain. For our study, the independent domain is obtained by the combination of the cited schemes with Independent Component Analysis (ICA). The Independent Component Analysis is used while inserting and extracting the message. Thus a performance compromise improvement of the original SCS and TCQ schemes in terms of robustness, capacity, and security is shown. Then the obtained schemes performances are compared to the Spread Transform (ST) based scheme well known for its proven good robustness properties. Our results show that, using watermarking with side information in independent domain permits to improve the global SCS and TCQ schemes performances. For example, in the case of SCS, by studying the Bit Error Rate (BER) in function of the watermark to noise ratio (WNR), the robustness has been improved by 20 dB (1 decade) when WNR is equal to 0 dB. Moreover, the capacity study shows for the same WNR=0 dB, the amount of information to be transmitted without error for a given noise level of the proposed SCS combined with ICA scheme (SCS-ICA) is much higher than that of the existing schemes. Finally, the study of the probability density functions (PDF) of the original and marked signals has shown that the Cachin-security level of the TCQ in an independent domain scheme (TCQ-ICA) is the best one compared to the other known schemes.     

网格编码矢量量化在SAR原始数据压缩中的应用

本文提出了一种结合传统的块自适应量化与网格编码矢量量化对SAR原始数据进行压缩的方法。首先对SAR原始数据实施块自适应量化以减小数据的动态范围,然后对块自适应量化后的数据进行网格编码矢量量化。该方法在考虑了SAR原始数据特性的基础上较好地利用了矢量的空间相关性和信号的时间相关性,进一步提高了量化增益。仿真结果表明,该方法在SAR原始数据的压缩中取得了很好的效果。     

基于变步长量化的安全图像隐写

图像隐写通过将信息隐藏在载体图像中进行秘密传送,实现隐蔽通信.提出了VSQS图像隐写算法,利用密钥控制生成高斯序列并取整,用于对经伪随机排列后的图像像素进行变步长量化,根据量化像素与秘密信息之间的关系来修改像素,实现信息的嵌入.同时给出了该算法的一种扩展(称为TLQS隐写).实验结果表明,VSQS和TLQS图像隐写可提供较大的隐藏容量,并能抵抗几种常见的隐写分析方法.     

冀南山区传统村落主街界面形态量化研究

针对传统村落保护与更新过程中其街巷界面形态出现同质化、雷同化、商品化等问题,基于冀南山区内与等高线平行、垂直、斜交三种类型的传统村落主街界面形态数据,采用分形理论、数理统计学等相关分析方法,量化描述了冀南山区传统村落主街底界面与侧界面的形态规律及其组构方式,总结出与一定量化参数区间所对应的传统村落主街界面形态特征。     

有限字长对自适应噪声对消器输出信噪比的限制

本文讨论了LMS自适应噪声对消器的有限字长效应。推导了包括量化噪声和截断噪声的输出信噪比的理论公式。如果某个量化字长能反映出输出弱信号的变化,输出信噪比主要取决于自适应运算的字长。     

Stabilization of multiple independent linear systems with control networks

The problem of stabilizing multiple independent linear systems sharing one conmmon network cable is presented and solved. Both the quanfization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quanfization and time sequencing, and the data rate is also presented in temps of the quanfization and time sequencing. A numerical example is given to illustrate the result.     

基于FPGA的关键词识别系统实现

随着微电子技术的高速发展,基于片上系统SOC的关键词识别系统的研究已成为当前语音处理领域的研究热点和难点。运用Xilinx公司ViterxII Pro开发板作为硬件平台,结合ISE10.1集成开发环境,完成了语音帧输出、MFCC、VQ和HMM等子模块的设计;提出了一种语音帧压缩模块架构,有效实现了语音帧信息到VQ标号序列的压缩,实现了由语音帧压缩模块和HMM模块构建的FPGA关键词识别系统。仿真实验结果表明,该系统具有较高的识别率和实时性,为关键词识别系统的FPGA硬件电路的实现研究提供了实例。     

通过外加扰动改善A／D变换器的传递特性

本文阐述了Ａ／Ｄ变换器量化误差的产生,在文献（１）的基础上讨论了Ａ／Ｄ变换器的输出平均量化误差与外加扰动之间的关系,并且利用了中心极限定理,通过多个扰动的合成,生成一个近似的正态分布的扰动,从而提高Ａ／Ｄ变换器的线性,这种扰动形式易于实现,方差可控,并且可以忽略高次谐波的干扰。     

Speed-up Technique for a Local Automatic Colour Equalization Model

In this paper we propose a speed‐up technique for a local automatic colour equalization operator derived from a model of the human vision system. This method is characterized by local and global filtering effects, that simultaneously achieve different equalization tasks e.g. performing colour and lightness constancy, realizing dynamic image data driven stretching, controlling the contrast. We describe a way to quickly create a filtering mapping function to perform the global component of the mapping. This method is based on singular value decomposition (SVD) applied to sampled and filtered points in the input image. Then, the local information is added computing the basic algorithm on a neighbourhood of each input pixel. A slight quality loss is the price that we have to pay for a speed‐up of more than two orders of magnitude of the basic algorithm. We present the results on several images and discuss the efficiency and the drawbacks of the speed‐up technique.