基于小波分解和RBF网络的三极管电路故障诊断

在分析现有三极管放大电路故障诊断算法不足的基础上,提出了一种基于模型的小波-RBF网络故障诊断算法。在PSPICE环境下建立三极管常见的故障模型,利用多层小波分解优异的时频特性提取故障特征参数,利用RBF强大的非线性分类能力和快速的收敛特性进行了典型共基极放大电路中三极管的软、硬故障诊断仿真。计算及仿真结果显示,这种故障诊断算法具有诊断速度快、诊断正确率高的特点。     

PSPICE在差分放大电路分析中的应用研究

差分放大电路作为集成运算放大器的输入级电路,具有电路结构复杂、分析繁琐的特点,一直是模拟电子技术设计与分析中的难点。PSPICE作为著名的电路设计与仿真软件,具有仿真速度快、精度高等优点。本文应用PSPICE对差分放大电路的工作特性进行了较全面的仿真,利用PSPICE分析、研究了差分放大电路的时域响应、频率响应以及温度对其性能的影响。     

旋转变压器信号的标定与解调

针对检波后信号存在直流偏置、幅值不等和相位偏移等问题,采用梯度估计算法,对检波后的包络信号进行离线标定;并设计了基于状态观测器的旋转变压器-数字转换(RDC)算法,对标定后的包络信号进行解调.试验结果表明,梯度估计算法收敛速度快,估计精度高.与反正切法相比,所设计的RDC算法不需通过数值差分即可获得角速度信息,干扰抑制能力强,角位置和角速度估计精度高.     

高频小信号放大器的设计与仿真

以FM广播频带小信号谐振放大器为例,对无线通信接收机中的高频小信号放大器进行设计与仿真研究,提出了高频小信号放大器的设计方法,采用PSPICE仿真软件对各部分电路进行了辅助设计分析,并对电路的通频带、选择性和功率增益等性能进行了仿真分析.结果表明,所设计的放大器满足预期设计指标要求,设计过程和方法都比较简单,仿真结果误差也很小,与传统的设计方法相比,解决了设计中运算量大,设计结果的硬件调整和测试都比较复杂且不易优化的问题.电路性能的仿真结果表明了方法的有效性.     

一种PSPICE辅助分析程序APSPICE

本文所论述的程序是对PSPICE软件的改进和补充。利用它可以非常简便地建立电路输入文件,解决了在选择电路元件模型参数,建立和修改电路输入文件中所遇到的困难;并使PSPICE所产生的输出文件汉字显示,使软件的中间和输出结果易读易懂。     

一种基于GEP的演化硬件复杂电路优化算法

演化硬件是近年来新兴的研究热点,它是演化算法和可编程逻辑器件相结合而形成的硬件设计新方法。在演化硬件中门电路的优化设计是一个重要的研究领域。提出一种新的基于基因表达式程序设计（GEP）的算法来进行复杂优化电路的设计,通过仿真实验表明,该算法不仅收敛速度快,而且还能利用该算法优化大规模的门电路,克服了传统优化方法的求解速度慢甚至不收敛等缺点。该算法较传统的电路优化方法更简单、更高效。     

基于OTA和CCCII的电流模式可调谐滤波器

设计了一种新颖的双二阶电流模式通用滤波器结构,该滤波器仅包含有源器件OTA、CCCII和接地电容,电路结构简单,与VLSI工艺兼容,便于集成,可实现同时低通、高通、带通、带阻、全通等滤波功能;Q和ω0可以互相不影响的独立调节。采用PSPICE软件仿真分析了所提电路的性能。     

改进暂态混沌神经网络在信道分配中的应用

研究信道分配优化问题,由于传统迭代过程中存在收敛率低,易于陷入局部最优解等缺点。为改善算法收敛速率和信道分配效果,采用改进的暂态混沌神经网络(MTCNN)。在混沌神经网络的动态特性中采用时变增益,在退火过程中采取分段的退火机制,使得混沌搜索阶段保持较长时间的混沌态,利于进行全局搜索,稳定收敛阶段能够迅速收敛于最优解,提高收敛率。仿真结果表明,改进后的算法能很好地解决信道分配问题。和暂态混沌神经网络及仅分段的暂态神经网络相比,最优解率得到很大的提高,网络收敛速度提高了12%以上。最后,给出了模型参数对网络性能影响的一些结论。     

集成模拟乘法器的调幅电路系统研究

在叙述调幅电路理论的基础上,提出集成模拟乘法器的调幅电路设计,建立了PSPICE的子电路模型.将模型添加至PSPICE模型数据库中,实现了高效率传输过程.四象限模拟乘法器电路的设计实现了因电压与电流的变化而导致乘法器出现精准度不足的问题.通过对电路系统进行仿真研究,满足了大众的需求,具有重要的研究意义.     

基于忆阻器的矩形波信号发生器

利用忆阻器独特的电路学性质,设计了一个基于忆阻器的新型矩形波信号发生器。电路中不含有分立的电容元件,输出波形频率和幅值精确可调。用PSPICE进行仿真分析,仿真结果验证了该方案的有效性。     

直流复杂电感电路本安性的瞬态分析

提出了直流复杂电路中电感支路电弧放电的抛物线模型，用＂模拟电源法＂对直流复杂电路的电感支路本质安全型进行瞬态分析。     

基于欧氏距离的矩形Packing问题的确定性启发式求解算法

使用拟人的策略,提出了基于欧氏距离的占角最大穴度优先的放置方法,为矩形Packing问题的快速求解提供了一种高效的启发式算法.算法的高效性通过应用于标准电路MCNC和GSRC得到了验证.     

A continuous DC programming approach for resource allocation in OFDMA/TDD wireless networks

The next generation broadband wireless networks deploys OFDM/OFDMA as the enabling technologies for broadband data transmission with QoS capabilities. Many optimization problems have arisen in the conception of such a network. This article studies an optimization problem in resource allocation. By using mathematical modeling technique we formulate the considered problem as a pure integer linear program. This problem is reformulated as a DC (Difference of Convex functions) program via an exact penalty technique. We then propose a continuous approach for its resolution. Our approach is based on DC programming and DCA (DC Algorithm). It works in a continuous domain, but provides integer solutions. To check globality of computed solutions, a global method combining DCA with a well adapted Branch-and-Bound (B&B) algorithm is investigated. Preliminary numerical results are reported to show the efficiency of the proposed method with respect to the standard Branch-and-Bound algorithm.     

Numerical methods for transient solutions of machine repair problems

This paper reviews and compares two types of numerical methods of computing transient probabilities of finite Markovian queues (particularly the machine repair problem). A brief review of each method is followed by numerical examples of small and moderate size machine repair problems. The results demonstrate the feasibility of applying numerical techniques for obtaining transient solutions to Markovian queueing problems.     

Lower bounds on precedence-constrained scheduling for parallel processors

We consider two general precedence-constrained scheduling problems that have wide applicability in the areas of parallel processing, high performance compiling, and digital system synthesis. These problems are intractable so it is important to be able to compute tight bounds on their solutions. A tight lower bound on makespan scheduling can be obtained by replacing precedence constraints with release and due dates, giving a problem that can be efficiently solved. We demonstrate that recursively applying this approach yields a bound that is provably tighter than other known bounds, and experimentally shown to achieve the optimal value at least 90.3% of the time over a synthetic benchmark.We compute the best known lower bound on weighted completion time scheduling by applying the recent discovery of a new algorithm for solving a related scheduling problem. Experiments show that this bound significantly outperforms the linear programming-based bound. We have therefore demonstrated that combinatorial algorithms can be a valuable alternative to linear programming for computing tight bounds on large scheduling problems.     

Evolutionary search for faces from line drawings

Single 2D line drawing is a straightforward method to illustrate 3D objects. The faces of an object depicted by a line drawing give very useful information for the reconstruction of its 3D geometry. Two recently proposed methods for face identification from line drawings are based on two steps: finding a set of circuits that may be faces and searching for real faces from the set according to some criteria. The two steps, however, involve two combinatorial problems. The number of the circuits generated in the first step grows exponentially with the number of edges of a line drawing. These circuits are then used as the input to the second combinatorial search step. When dealing with objects having more faces, the combinatorial explosion prevents these methods from finding solutions within feasible time. This paper proposes a new method to tackle the face identification problem by a variable-length genetic algorithm with novel heuristic and geometric constraints incorporated for local search. The hybrid GA solves the two combinatorial problems simultaneously. Experimental results show that our algorithm can find the faces of a line drawing having more than 30 faces much more efficiently. In addition, simulated annealing for solving the face identification problem is also implemented for comparison.     

面向离散优化问题的量子协同演化算法

为解决现有离散优化算法在有限时间内容易出现过早收敛或难以收敛的问题,提出了面向离散优化问题的量子协同演化算法。该算法通过种群初始化策略构建分布均匀的初始种群,并改进粒子群和单点优化算法成为具有不同搜索能力的协同演化策略,进而利用量子旋转门根据种群个体的进化情况自适应地选择合适的演化策略,最后利用精英保持策略避免种群的退化。在标准离散问题和背包问题的测试环境中,各算法的平均收敛精度和实际收敛情况均表明,已提出的算法能够在有限时间内,收敛到精度较高的解,可用于求解具有时效要求的离散优化问题。     

基于拟人策略的带有预放置模块的布局算法

在超大规模集成电路设计中，一些特别重要的模块，像RAM、ROM和CPU等经常被优先放置，而其它模块则被两两互不重叠地放置在芯片的剩余区域。此类问题能被形式化为带有预放置模块的布局问题，关于此问题的求解方法多为随机优化方法。该文基于拟人的思想，提出了占角和最大穴度优先的放置策略，为该问题的快速求解提供了一种高效的启发式确定性算法。算法的高效性通过应用于标准电路MCNC得到了验证。     

Analysis of nonlinear electrical circuits using bernstein polynomials

In electrical circuit analysis, it is often necessary to find the set of all direct current (d.c.) operating points (either voltages or currents) of nonlinear circuits. In general, these nonlinear equations are often represented as polynomial systems. In this paper, we address the problem of finding the solutions of nonlinear electrical circuits, which are modeled as systems of n polynomial equations contained in an n-dimensional box. Branch and Bound algorithms based on interval methods can give guaranteed enclosures for the solution. However, because of repeated evaluations of the function values, these methods tend to become slower. Branch and Bound algorithm based on Bernstein coefficients can be used to solve the systems of polynomial equations. This avoids the repeated evaluation of function values, but maintains more or less the same number of iterations as that of interval branch and bound methods. We propose an algorithm for obtaining the solution of polynomial systems, which includes a pruning step using Bernstein Krawczyk operator and a Bernstein Coefficient Contraction algorithm to obtain Bernstein coefficients of the new domain. We solved three circuit analysis problems using our proposed algorithm. We compared the performance of our proposed algorithm with INTLAB based solver and found that our proposed algorithm is more efficient and fast.