网络化控制系统中状态估计策略的进展

在网络化控制系统(Networked Control Systems,简记为NCSs)中,由于网络的介入使控制系统的规模和复杂性显著增加,且产生了各种新问题,为了使控制更加容易,需要设计合理的估计策略.主要从控制和通信2个角度出发,集中考虑了在量化影响、时延与丢包、不确定性等通信受限因素下状态估计策略的研究与进展.一直以来,状态估计都是诸如过程监控、故障诊断等控制领域中不可缺少的重要部分,当前已成为网络化控制系统研究的热点和准点,为抵消网络环境不确定性对闭环系统性能的影响,设计最优的状态估计策略必将成为不可缺少的因素之一.     

A quantized set-membership estimation-based heading control method of unmanned surface vessels under unknown-but-bounded wave-induced disturbances

This paper is concerned with the heading tracking control problem for a network-based unmanned surface vessel (USV) under wave-induced disturbances. Considering the characteristics of the wave-induced disturbances, the unknown-but-bounded (UBB) noise model is adopted. Meanwhile, signal quantization is taken into account due to the limited capacity of the communication channel. Based on these considerations, a novel set-membership based control scheme is proposed, which consists of a set-membership filter (SMF) and a set-membership controller (SMC). In the proposed control scheme, the SMF is designed for providing an ellipsoidal estimation set for the USV at each sampling step, and then the SMC uses the estimation set for producing control input for the USV in order to track the reference. Sufficient conditions are derived for the considered USV system to be asymptotically stable and satisfy the modified set-membership performance constraint. Simulation results verifies the effectiveness of the proposed control scheme.     

On the design of compensator for quantization-caused input-output deviation

This paper considers the design of compensators for systems with quantized inputs in order to reduce the influence of quantization.For systems with (vector) relative degrees,we propose a kind of compensators which can compensate for the accumulated output deviation completely caused by quantization.The proposed compensators are capable of keeping the differences of the input-output responses between the systems with quantized inputs and the original systems without considering quantization within certain sm...     

Lapped transform‐based codec for frame‐memory reduction in super‐quality LCD overdrive

Abstract— Overdrive is commonly used to reduce the liquid‐crystal response time and motion blur in liquid‐crystal displays (LCDs). However, overdrive requires a large frame memory in order to store the previous frame for reference. In this paper, a lapped transform‐based codec (LTC) is proposed to reduce the frame memory needed for LCD overdrive. In the latest literature, a directional prediction‐based codec (DPC) employs eight directional predictions, which takes up a large percentage of the computational complexity of the codec and does not consider the de‐correlation of the inter‐blocks. Therefore, the LTC first uses the lapped transform to decompose the correlation of the inter‐blocks in the YUV color space. A hadamard transform is then used for energy compaction. The reordered coefficients are pre‐quantized and encoded using the proposed adaptive bit‐plane coding (ABPC) method for a simple hardware implementation. The simulation results show that the proposed LTC significantly improves the DPC in both subjective and objective performance and outperforms the block truncation coding (BTC) and adaptive multi‐level BTC (AM‐BTC), which have been described in the literature.     

基于图像先验知识的量化噪声盲估计算法

经过离散余弦变换的图像在DCT域系数的分布近似符合一个用参数λ描述的拉普拉斯分布。利用该参数以及图像在JPEG压缩中使用的DCT域量化系数,可以实现对图像量化噪声的估计。提出一种基于图像先验知识的分布参数估计方法,可以在没有未压缩的原始图像作为参考时实现对λ值的估计,进而计算压缩图像的峰值信噪比。     

基于QFD和TRIZ理论相结合的产品质量的评估方法研究

现代社会消费者对产品的评价指标是衡量产品质量优劣的标准,如何对消费者的需求进行科学的评估成为提升产品质量,推动企业进步的一项重要因素。文章结合QFD和TRIZ理论的研究方式,将顾客的感性需求进行量化分析,为产品质量评估提供了量化的理论与方法,并通过实例进行合理的分析论证。     

基于奇偶量化的彩色图像盲水印算法

提出一种基于奇偶量化的彩色图像小波域的数字水印算法。首先对水印图像进行置乱处理,然后对图像进行翻转,最后利用混沌系统产生的混沌序列对水印进行加密。水印嵌入时,采用小波变换并利用奇偶量化规则将加密后的水印嵌入到载体图像蓝色分量最深层的四个子带中。水印提取时,不需要原始图像的参与,实现了盲提取。仿真实验和性能分析表明,该算法有很好的不可见性和鲁棒性,可以有效地抵抗JPEG压缩、噪声、剪切等攻击。     

Rolling element bearing fault diagnosis using wavelet transform

This paper is focused on fault diagnosis of ball bearings having localized defects (spalls) on the various bearing components using wavelet-based feature extraction. The statistical features required for the training and testing of artificial intelligence techniques are calculated by the implementation of a wavelet based methodology developed using Minimum Shannon Entropy Criterion. Seven different base wavelets are considered for the study and Complex Morlet wavelet is selected based on minimum Shannon Entropy Criterion to extract statistical features from wavelet coefficients of raw vibration signals. In the methodology, firstly a wavelet theory based feature extraction methodology is developed that demonstrates the information of fault from the raw signals and then the potential of various artificial intelligence techniques to predict the type of defect in bearings is investigated. Three artificial intelligence techniques are used for faults classifications, out of which two are supervised machine learning techniques i.e. support vector machine, learning vector quantization and other one is an unsupervised machine learning technique i.e. self-organizing maps. The fault classification results show that the support vector machine identified the fault categories of rolling element bearing more accurately and has a better diagnosis performance as compared to the learning vector quantization and self-organizing maps.     

Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis

The quick advance in image/video editing techniques has enabled people to synthesize realistic images/videos conveniently. Some legal issues may arise when a tampered image cannot be distinguished from a real one by visual examination. In this paper, we focus on JPEG images and propose detecting tampered images by examining the double quantization effect hidden among the discrete cosine transform (DCT) coefficients. To our knowledge, our approach is the only one to date that can automatically locate the tampered region, while it has several additional advantages: fine-grained detection at the scale of 8×8 DCT blocks, insensitivity to different kinds of forgery methods (such as alpha matting and inpainting, in addition to simple image cut/paste), the ability to work without fully decompressing the JPEG images, and the fast speed. Experimental results on JPEG images are promising.     

An improved lossless data hiding scheme based on image VQ-index residual value coding

Copyright protection and information security have become serious problems due to the ever growing amount of digital data over the Internet. Reversible data hiding is a special type of data hiding technique that guarantees not only the secret data but also the cover media can be reconstructed without any distortion. Traditional schemes are based on spatial, discrete cosine transformation (DCT) and discrete wavelet transformation (DWT) domains. Recently, some vector quantization (VQ) based reversible data hiding schemes have been proposed. This paper proposes an improved reversible data hiding scheme based on VQ-index residual value coding. Experimental results show that our scheme outperforms two recently proposed schemes, namely side-match vector quantization (SMVQ)-based data hiding and modified fast correlation vector quantization (MFCVQ)-based data hiding.