Genetic algorithm‐based neural‐network modeling approach applied to AlGaN/GaN devices

An accurate equivalent circuit large‐signal model (ECLSM) for AlGaN‐GaN high electron mobility transistor (HEMT) is presented. The model is derived from a distributed small‐signal model that efficiently describes the physics of the device. A genetic neural‐network‐based model for the gate and drain currents and charges is presented along with its parameters extraction procedure. This model is embedded in the ECLSM, which is then implemented in CAD software and validated by pulsed and continuous large‐signal measurements of on‐wafer 8 × 125‐μm GaN on SiC substrate HEMT. Pulsed IV simulations show that the model can efficiently describe the bias dependency of trapping and self‐heating effects. Single‐ and two‐tone simulation results show that the model can accurately predict the output power and its harmonics and the associated intermodulation distortion (IMD) under different input‐power and bias conditions. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

一种改进编码器角度解算过程的方法与实现

在机械电子一直是一个热门学科,其目的是通过软件控制机械操作来代替机械的哑巴解决方案。DS-25旋转电子编码器能够很好地与机械电子应用相匹配,其输出为两路标准的sine和cosine曲线,通过分析sine和cosine数值来计算编码器所对应的绝对角度位置。通过对DS-25的工作模式分析和实际应用情况提出角度解算的改进方案,该方案利用DS-25工作于粗略模式下测试到的角度值来推算精确模式下的信号周期,结合精确模式下测试到的角度值来计算编码器所对应的绝对角度。摒弃其原有的复杂查表过程进而节省电子表格的存储空间,在降低硬件成本的同时提升了软件灵活性。实验证明,算法的改进能够节省约2KB的存储空间,角度位置误差能控制在1‰以内。     

弹体撞击钢板过载信号处理方法

弹体在跌落撞击钢板过程中,弹体上将会叠加非常复杂的震荡信号,这些震荡信号对实际过载信号的提取和分析将造成不可忽视的影响.本文通过将实弹跌落至钢板,采集到弹体在碰撞钢板过程中的过载信号和弹体上的各阶震荡信号,并对这些震荡信号进行频谱分析和ANSYS有限元模态分析,为弹体的碰撞过载数据分析提供了帮助.     

Turbo spin-echo sequences in magnetic resonance imaging of the brain: Physics and applications

Fast SE imaging provides considerable measure time reduction, high signal-to-noise ratios as well as similar contrast behavior compared to conventional SE sequences. Besides TR and TE_eff, echo train length (ETL), interecho time , and-space trajectory determine image contrast and image quality in fast SE sequences. True proton density contrast (CSF hypointense) and not too strong T2 contrast are essential requirements in routine brain MRI. A Turbo SE sequence with very short echo train length (ETL=3), short TE_eff and short interecho time (17 ms), and TR=2000 ms was selected for proton density contrast; a Turbo SE sequence with ETL=7, TE_eff=90 ms, =22 ms, and TR=3250 ms was selected for T₂-weighted images. Using both single-echo Turbo SE sequences yielded 50% measure time reduction compared to the conventional SE technique. Conventional SE and optimized Turbo SE sequences were compared in 150 patients resulting in very similar signal and contrast behavior. Furthermore, reduced flow artifacts in proton density—and especially in T₂-weighted Turbo SE images—and better contrast of high-intensity lesions in proton density-weighted Turbo SE images were found. Slightly reduced edge sharpness—mainly in T₂-weighted Turbo SE images—did not reduce diagnostic reliability. Differences between conventional and Turbo SE images concerning image contrast and quality are explained regarding special features of fast SE technique.Address for correspondence: Institut für Röntgendiagnostik, Klinikum der Universität Regensburg, Franz-Josef-Strauß-Allee 11, 93042 Regensburg, Germany. Additional reprints of this chapter may be obtained from the Reprints Department, Chapman & Hall, One Venn Plaza, New York, NY 10119.     

Tariff reduction as a tool to increase the efficiency of electricity distributors: A case study in southern Brazil

The article aims to evaluate the consumer response to a reduction in the electricity tariffs as a hourly economic signal for the case of an electric utility in the state of Rio Grande do Sul, southern Brazil. Using Differences-in-differences method, the results were robust in showing that the change in the economic signal increased up to 81.01% the consumption at the time influenced by the change, improving the way in which the company's assets are used, in addition to reducing fuel oil consumption by users.     

智能车竞赛中道路的视频识别方案

视频信号的的采集和处理是一个复杂的过程,这需要程序设计者了解视频信号的构成,充分利用复合视频信号中的各种同步信息作为视频信号采集的控制信号,从而完成信号的采集。     

Stabilizing switching design for switched linear systems: A state-feedback path-wise switching approach

This paper addresses the problem of switching stabilization for discrete-time switched linear systems. Based on the abstraction-aggregation methodology, we propose a state-feedback path-wise switching law, which is a state-feedback concatenation from a finite set of switching paths each defined over a finite time interval. We prove that the set of state-feedback path-wise switching laws is universal in the sense that any stabilizable switched linear system admits a stabilizing switching law in this set. We further develop a computational procedure to calculate a stabilizing switching law in the set.     

Mathematical methods of geoinformatics. III. Fuzzy comparisons and recognition of anomalies in time series

The search for anomalies in time series by methods of fuzzy logic is further explored. The algorithms DRAS and FLARS underlying these methods are further developed in the form of the algorithm FCARS that is completely based on fuzzy comparisons. Parts 1 and 2 were published in Cybernetics and Systems Analysis, No. 2, 2002 and No. 4, 2003. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 3–18, May–June 2008.     

智能电源系统在信号领域中的应用

随着轨道交通的发展,信号设备要求具备智能化、模块化、自动化、网络化的智能电源系统。针对信号系统的发展对智能电源系统的要求,阐述了智能电源系统在智能化、模块化、自动化三方面的应用。介绍了目前智能电源系统所采用各种不同的技术方案,并论述了方案的优缺点,总结了目前存在的问题和发展方向。     

Parallel Implementation of a Class of Adaptive Signal Processing Applications

Recently, High Performance Computing (HPC) platforms have been employed to realize many computationally demanding applications in signal and image processing. These applications require real-time performance constraints to be met. These constraints include latency as well as throughput. In order to meet these performance requirements, efficient parallel algorithms are needed. These algorithms must be engineered to exploit the computational characteristics of such applications. In this paper we present a methodology for mapping a class of adaptive signal processing applications onto HPC platforms such that the throughput performance is optimized. We first define a new task model using the salient computational characteristics of a class of adaptive signal processing applications. Based on this task model, we propose a new execution model. In the earlier linear pipelined execution model, the task mapping choices were restricted. The new model permits flexible task mapping choices, leading to improved throughput performance compared with the previous model. Using the new model, a three-step task mapping methodology is developed. It consists of (1) a data remapping step, (2) a coarse resource allocation step, and (3) a fine performance tuning step. The methodology is demonstrated by designing parallel algorithms for modern radar and sonar signal processing applications. These are implemented on IBM SP2 and Cray T3E, state-of-the-art HPC platforms, to show the effectiveness of our approach. Experimental results show significant performance improvement over those obtained by previous approaches. Our code is written using C and the Message Passing Interface (MPI). Thus, it is portable across various HPC platforms. Received April 8, 1998; revised February 2, 1999.