FSM自动综合输入系统的设计

实现有限状态机(FSM)的自动逻辑综合,是全面完成数字系统逻辑设计自动化的一条最直接有效的途径。FSM自动综合的描述输入子系统是整个FSM自动综合过程中首要和关键的一个环节。本文将比较详细地介绍和讨论FSM自动综合之描述输入子系统的各个组成部分:①类C FSM功能描述语言cfdl的设计及其文本编制;②cfdl词法及语法分析和检查;③FSM状态关系的析离;④内部格式的转换;⑥状态间逻辑条件的验证。     

一种扩展的朴素贝叶斯分类器改进算法

文中研究贝叶斯分类器家族中的一种扩展朴素贝叶斯分类器。此种扩展朴素贝叶斯分类器满足两个条件:一是类结点是所有属性的父结点;二是每个属性最多有一个属性父结点。其中有代表性的两种算法是贪婪爬山算法(Hill Climb-ing Search,即HCS算法)和超父结点算法(Superparent,即SP算法)。对两种算法进行了分析和比较,并在此基础上提出了一种改进算法。通过实验验证所改进的分类器是正确的、有效的。     

FSM状态间逻辑条件检验的算法研究

有限状态机(FSM)是VLSI控制结构的一种映射,它的自动综合成为设计自动化的一个十分重要的环节和途径。本文讨论在FSM自动综合中输入阶段的状态间逻辑条件检验的问题,研究分析状态间逻辑条件检验的相互关系及影响,并提出了FSM状态间逻辑条件检验的优化算法,从而使时间复杂度降低,实现更加简便。最后,本文给出了优化算法的流程和一些实验结果,结果令人满意。     

一种新的删除HB(κ)树的结点的算法

Foster的删除HB(κ)树的结点的算法的主要思想是先删除结点再自下而上处理某些子树,涉及自下而上的后退.提出一种新的删除HB(κ)树的结点的算法,其主要思想是先自上而下处理某些子树再删除结点,不涉及自下而上的后退.举例说明新算法的执行过程.证明新算法是正确的.与Foster的删除HB(κ)树的结点的算法相比,新算法不涉及辅助栈的使用.设n是HB(κ)树的结点的个数.新算法的时间复杂性是0(log2n),与Foster的删除HB(κ)树的结点的算法的相同.实验结果表明新算法的平均执行对间比Foster的删除HB(κ)树的结点的算法短.新算法的空间复杂性是O(1),比Foster的删除HB(κ)树的结点的算法低.     

基于局域网的系统级概率分布式故障诊断

提出了一个系统级概率分布式故障诊断的算法 ,它能诊断局域网及其类似系统中结点机故障和链路故障 .该算法突破了现有研究成果中要求网络中故障结点数不超过 t(t相似文献   

基于FSM的协议形式化技术研究

本文主要讨论基于有限状态机(FSM)的协议形式化技术问题。文中论述了FSM形式描述与验证的技术特征,提出了一种增强FSM形式化方法,并给出了基于该方法的形式描述与验证的协议实例。     

SoC高级综合验证研究进展

针对近年来片上系统(system on chip,SoC)高级综合验证领域的工作,首先分析了高级综合验证的难点,然后根据应用领域将算法分为3类:高级综合前端验证算法、高级综合调度验证算法和高级综合后端验证算法.同时分析了各类算法的优缺点和现有算法的主要技术手段;最后讨论了SoC高级综合验证算法目前面临的映射关系缺失、状态空间爆炸和复杂的数据结构等挑战,并对该领域今后的研究方向进行了展望.     

嵌入式开发过程中按键检测算法的改进

为了解决嵌入式系统开发过程中,传统按键检测算法将单片机的资源全部用来做按键扫描,从而使CPU的利用率大大降低的问题。在传统按键检测算法的基础上,提出了一种基于有限状态机(FSM)的按键检测程序算法。为了验证基于FSM的按键检测程序算法较传统算法的优势,在Keil uVison3集成开发坏境下,将两种算法做了性能分析。通过性能分析窗口,可以看出新算法在CPU利用率方面得到了大大的提高。     

基于频繁模式树的分布式关联规则挖掘算法

提出一种基于频繁模式树的分布式关联规则挖掘算法(DMARF).DMARF算法设置了中心结点,利用局部频繁模式树让各计算机结点快速获取局部频繁项集,然后与中心结点交互实现数据汇总,最终获得全局频繁项集.DMARF算法采用顶部和底部策略,能大幅减少候选项集,降低通信量.理论分析和实验结果均表明了DMARF算法是快速而有效的.     

有限状态机的VHDL描述及综合

介绍了使用VHDL描述有限状态机的方法,重点分析了综合过程中的竞争和毛刺现象产生的原因,并提供了解决方法。最后以图形学中的直线算法为例实现了可综合的FSM描述,并通过门级仿真验证了其正确性。     

基于状态翻转连续长度码的测试数据压缩和解压

提出了新一类的变-变长度压缩码，称之为状态翻转连续长度码。该文在测试序列中直接编码连续的“0”和“1”的长度，压缩一个预先计算的测试集，无需像其它文章中受限制仅仅编码连续的“0”，又解决了交替-连续长度码中对两个相邻的连续序列进行编码时必须附加一位的问题。该方法的解压结构是一个简单的有限状态机，不需要一个与扫描链等长的循环扫描移位寄存器。实验结果表明，这种编码能够有效地压缩测试数据。     

Road network extraction: a neural-dynamic framework based on deep learning and a finite state machine

Extracting road networks from very-high-resolution (VHR) aerial and satellite imagery has been a long-standing problem. In this article, a neural-dynamic tracking framework is proposed to extract road networks based on deep convolutional neural networks (DNN) and a finite state machine (FSM). Inspired by autonomous mobile systems, the authors train a DNN to recognize the pattern of input data, which is an image patch extracted in a detection window centred at the current location of the tracker. The pattern is predefined according to the environment and associated with the states in the FSM. A vector-guided sampling method is proposed to generate the training data set for the DNN, which extracts massive image-direction pairs from the imagery and existing vector road maps. In the tracking procedure, the size of the detection window is determined by a fusion strategy and the extracted image patches represent the orientation features of the road (local environment) that can be recognized by the trained DNN. The reactive unit in FSM associates states with behaviours of the tracker while continually modifying the orientation to follow the road and generating a sequence of states and locations. In this way, our framework combines the DNN and FSM. DNN acts as a key component to recognize patterns from a complex and changing environment; FSM translates the recognized patterns to states and controls the behaviour of the tracker. The results illustrate that our approach is more accurate and efficient than the traditional ones.     

SoC有限状态机优化验证方法研究

利用图论及数学规划方法分析并解决有限状态机验证路径的选择优化,提出一种在仿真验证方法中对SOC有限状态机验证路径进行优化的方法．在C＊Core提供的验证环境中,对其部分Golden File验证任务的有限状态机进行了优化处理,通过原方案的验证时间的对比,表明了该方法可以使用更短的时间有效解决有限状态机验证问题．     

Minimization of mealy finite-state machines by using the values of the output variables for state assignment

Structural models of finite-state machines (FSMs) that make it possible to use the values of the output variables for encoding the internal states are studied. To minimize the area (the parameter area is used to denote cost in the context of this paper) of FSM implementation, it is proposed to use the structural model of the class D FSM. A method for the design of the class D FSM in FPGA is proposed. This method involves two phases—splitting the internal states of the FSM (to satisfy the necessary conditions for the construction of the class D FSM) and encoding the internal states (to ensure that the codes are mutually orthogonal). It is shown that the proposed method reduces the area of FSM implementation for all families of FPGAs of various manufacturers by a factor of 1.41–1.72 on average and by a factor of two for certain families. Practical issues concerning the method and the specific features of its use are discussed, and possible directions of the elaboration of this approach are proposed.     

Database design and querying within the fuzzy semantic model

Fuzzy semantic model (FSM) is a data model that uses basic concepts of semantic modeling and supports handling fuzziness, uncertainty and imprecision of real-world at the attribute, entity and class levels. The paper presents the principles and constructs of the FSM. It proposes ways to define the membership functions within all the constructs of the FSM. In addition, it provides a proposal for specifying FSM schema and introduce a query language adapted to FSM-based databases.     

Modeling of a dynamic dual-input dual-output fast steeringmirror system

A modeling method is proposed for a dynamic fast steering mirror (FSM) system with dual inputs and dual outputs. A physical model of the FSM system is derived based on first principles, describing the dynamics and coupling between the inputs and outputs of the FSM system. The physical model is then represented in a state-space form. Unknown parameters in the state-space model are identified by the subspace identification algorithm, based on the measured input-output data of the FSM system. The accuracy of the state-space model is evaluated by comparing the model estimates with measurements. The variance-accounted-for value of the state-space model is better than 97%, not only for the modeling data but also for the validation data set, indicating high accuracy of the model. Comparison is also made between the proposed dynamic model and the conventional static model, where improvement in model accuracy is clearly observed. The model identified by the proposed method can be used for optimal controller design for closed-loop FSM systems. The modeling method is also applicable to FSM systems with similar structures.     

Five-stage Milstein methods for SDEs

In this paper, we consider the problem of computing numerical solutions for Itô stochastic differential equations (SDEs). The five-stage Milstein (FSM) methods are constructed for solving SDEs driven by an m-dimensional Wiener process. The FSM methods are fully explicit methods. It is proved that the FSM methods are convergent with strong order 1 for SDEs driven by an m-dimensional Wiener process. The analysis of stability (with multidimensional Wiener process) shows that the mean-square stable regions of the FSM methods are unbounded. The analysis of stability shows that the mean-square stable regions of the methods proposed in this paper are larger than the Milstein method and three-stage Milstein methods.     

应用模逆运算的移动互联网可信终端设计方法

针对移动互联网海量移动终端用户的可信接人问题提出了一种芯片加密的可信接人系统的设计方案。首先将移动终端的可信接人过程划分为硬件预处理和可信接入两个子系统;在硬件预处理部分将有限状态机的思想用于模逆运算电路控制子系统的状态描述;而在可信接入部分基于Verilog语言将模拟运算电路抽象为控制系统状态转移图,再运用Verilog语言中的always模块将其转换为Moore型有限状态机,同时采用寄存器同步稳定输出控制信号,有效地实现了移动互联网终端设备的可信接入问题。仿真实验表明文中方法不仅能实现控制信号的输出与状态同步,还能避免组合输出产生的延迟及竞争与冒险现象,使终端设备的接入过程更加高效、稳定和可靠。