Adaptive boundary control for unstable parabolic PDEs—Part II: Estimation-based designs

The certainty equivalence approach to adaptive control is commonly used with two types of identifiers: passivity-based identifiers and swapping identifiers. The “passive” (also known as “observer-based”) approach is the prevalent identification technique in existing results on adaptive control for PDEs but has so far not been used in boundary control problems. The swapping approach, prevalent in finite-dimensional adaptive control is employed here for the first time in adaptive control of PDEs. For a class of unstable parabolic PDEs we prove a separation principle result for both the passive and swapping identifiers combined with the backstepping boundary controllers. The result is applicable in any dimension. For physical reasons we restrict our attention to dimensions no higher than three. The results of the paper are illustrated by simulations.     

低剂量X射线照射诱导HeLa细胞存活的

采用集落形成法观察了低剂量X射线照射HeLa细胞的存活率，结果表明，小于0．5Gy的X射线照射细胞的存活率高于对照，得到了HeLa细胞存活的“兴奋效应”，而且在0．25Gy附近这种效应更为明显；低剂量D1（0．05，0．75Gy)的预照射降低了随后攻击量D2对细胞的损伤程度，反映出低剂量照射可诱发细胞存活的“适应性反应”。     

Automatic playlist generation based on tracking user’s listening habits

Algorithms for automatic playlist generation solve the problem of tedious and time consuming manual selection of musical playlists. These algorithms generate playlists according to the user’s music preferences of the moment. The user describes his preferences either by manually inputting a couple of example songs, or by defining constraints for the choice of music. The approaches to automatic playlist generation up to now were based on examining the metadata attached to the music pieces. Some of them took also the listening history into account. But anyway, a heavy accent has been put on the metadata, while the listening history, if it was used at all, had a minor role. Missings and errors in metadata frequently appear, especially when the music is acquired from the Internet. When the metadata is missing or wrong, the approaches proposed so far cannot work. Besides, entering constraints for the playlist generation can be a difficult activity. In our approach we ignored the metadata and focused on examining the listening habits. We developed two simple algorithms that track the listening habits and form a listener model—a profile of listening habits. The listener model is then used for automatic playlist generation. We developed a simple media player which tracks the listening habits and generates playlists according to the listener model. We tried the solution with a group of users. The experiment was not a successful one, but it threw some new light on the relationship between the listening habits and playlist generation.     

On-line emission and economic load dispatch using adaptive Hopfield neural network

This paper presents an adaptive Hopfield neural network (AHNN) based methodology, where the slope of the activation function is adjusted, for finding approximate Pareto solutions for the multi-objective optimization problem of emission and economic load dispatch (EELD). We have placed emphasis on finding solutions quickly, rather than the global Pareto solutions, so that our algorithm can be employed in large on-line power systems where variations in load are quite frequent. To enable faster convergence, adaptive learning rates have been developed by using energy function and applied to the slope adjustment method. The proposed algorithm has been tested on selected IEEE bus benchmark systems. The convergence of AHNN is found to be nearly 50% faster than the non-adaptive version.     

Proactive resource allocation for asynchronous real-time distributed systems in the presence of processor failures

We present two proactive resource allocation algorithms, RBA^*-FT and OBA-FT, for fault-tolerant asynchronous real-time distributed systems. The algorithms consider an application model where task timeliness is specified by Jensen's benefit functions and the anticipated application workload during future time intervals is described by adaptation functions. In addition, we assume that reliability functions of processors are available a priori. Given these models, our objective is to maximize aggregate task benefit and minimize aggregate missed deadline ratio in the presence of processor failures. Since determining the optimal solution is computationally intractable, the algorithms heuristically compute sub-optimal resource allocations, but in polynomial time. Experimental results reveal that RBA^*-FT and OBA-FT outperform their non-fault-tolerant counterparts in the presence of processor failures. Furthermore, RBA^*-FT performs better than OBA-FT, although OBA-FT incurs better worst-case and amortized computational costs. Finally, we observe that both algorithms robustly withstand errors in the estimation of anticipated failures.     

基于非锐化掩模的实时自适应图像增强算法

针对传统的非锐化掩模算法的局限性,依据图像中各像素点及以其为中心的若干相邻像素点的均方差值,提出了自适应图像增强算法的原理,并分析其硬件实现方法,然后给出了该算法与其它算法应用于图像增强的对比结果,最后在FPGA（field programmable gate array）实验板上进行验证.实验结果表明,此算法有效的增强图像的细节区域,防止图像边缘区域出现过冲现象,抑制图像平坦区域的噪声放大.因此,该算法取得了良好的视觉效果,硬件实现简单,适合于实时条件下图像的增强.     

利用非线性自适应技术检测微弱的瞬时信号

本文根据局部流形理论,提出了一类非线性自适应预测滤波模型。仿真结果显示,本文提出的自适应预测滤波模型具有很强的非线性近似能力,可以检测淹没在超混沌或杂波环境中的瞬时信号。     

支持下一代无线宽带应用自适应QoS模型的研究

作为真正完整的下一代网络 ( NGN,Next Generation Network)解决方案 ,NGN需要在固定通信领域和移动通信领域都能够支持综合多媒体特性。NGN中的新一代移动通信网承载在开放式、层次化结构的分组交换网络之上 ,能够为用户提供端到端的 Qo S解决方案。本文分析了下一代移动通信系统中多媒体宽带应用的 Qo S问题 ,从无线通信系统的多层次结构出发 ,建立了业务流的 Qo S指标评判体系 ,为下一代网络中的无线宽带应用提供了一种自适应Qo S控制模型     

Robustness of VS-MRAC with respect to unmodelled dynamics and external disturbances

A variable structure model reference adaptive controller (VS-MRAC) using only input and output measurements was recently proposed and shown to be globally asymptotically stable with superior transient behaviour and disturbance rejection properties. In this paper a singular perturbation approach is used in order to establish the robustness of the controller in the presence of unmodelled dynamics (parasitics) and disturbances. We develop a new Lyapunov-based technique to analyse the overall system and show that for sufficiently small parasitics the system remains stable and the output error is small in some sense.     

自适应有源噪声控制的滤波-LMAD算法

本文研究了稳定非高斯环境下的自适应有源噪声控制问题，提出了滤波－ＬＭＡＤ（ｌｅａｓｔｍｅａｎａｂｓｏｌｕｔｅｄｅｖｉａｔｉｏｎ）算法及归一化滤波－ＬＭＡＤ算法，仿真结果表明，与常用的滤波－ＬＭＳ算法和归－化滤波－ＬＭＳ算法相比，本文提出了算法收敛速度更快。