查询词典 neural network

The operating principles of the monolayer neural network, Adeline network and B-P network in the system identification are introduced in this paper.

主要研究了单层神经网络、Adaline网络及B-P网络用于系统辨识中的工作原理，提出了把B-P网络权值转换为传递函数的方法。

In Black-Scholes pricing model, there was five variables impact the option price that we take to be the input variable in artificial neural network, both Back-Propagation Network and Radial Basis Function Network are used. Base on the difference analysis, we find out another variable that can improve learning efficiency and affectivity.

为避免差异，以Black-Scholes模式中，五项影响权证价格之因子为输入变数，分别以倒传递网路与半径式函数网路建立模式，並藉差异分析找出可改善学习绩效之变数。

PART 1 UNIT 1 B Electrical and Electronic Engineering Basics A Electrical Networks ———————————— 3 Three-phase Circuits A The Operational Amplifier ——————————— 5 UNIT 2 B Transistors A Logical Variables and Flip-flop —————————— 8 UNIT 3 B Binary Number System A Power Semiconductor Devices —————————— 11 UNIT 4 B Power Electronic Converters A Types of DC Motors —————————————15 UNIT 5 B Closed-loop Control of DC Drivers A AC Machines ———————————————19 UNIT 6 B Induction Motor Drive A Electric Power System ————————————22 UNIT 7 B PART 2 UNIT 1 B Power System Automation Control Theory A The World of Control ————————————27 —————29 The Transfer Function and the Laplace Transformation UNIT 2 B A Stability and the Time Response ————————— 30 Steady State————————————————— 31 A The Root Locus ————————————— 32 ————— 33 UNIT 3 B The Frequency Response Methods: Nyquist Diagrams UNIT 4 A The Frequency Response Methods: Bode Piots ————— 34 B Nonlinear Control System 37 UNIT 5 A Introduction to Modern Control Theory B State Equations 40 38 UNIT 6 A Controllability, Observability, and Stability B Optimum Control Systems UNIT 7 A Conventional and Intelligent Control B Artificial Neural Network Computer Control Technology A Computer Structure and Function 42 B Fundamentals of Computer and Networks 43 44 PART 3 UNIT 1 UNIT 2 A Interfaces to External Signals and Devices B The Applications of Computers 46 UNIT 3 A PLC Overview B PACs for Industrial Control, the Future of Control UNIT 4 A Fundamentals of Single-chip Microcomputer 49 B Understanding DSP and Its Uses 1 UNIT 5 A A First Look at Embedded Systems B Embedded Systems Design Process Control A A Process Control System B 50 PART 4 UNIT 1 Fundamentals of Process Control 52 53 UNIT 2 A Sensors and Transmitters B Final Control Elements and Controllers UNIT 3 A P Controllers and PI Controllers B PID Controllers and Other Controllers UNIT 4 A Indicating Instruments B Control Panels Control Based on Network and Information A Automation Networking Application Areas B Evolution of Control System Architecture PART 5 UNIT 1 UNIT 2 A Fundamental Issues in Networked Control Systems B Stability of NCSs with Network-induced Delay UNIT 3 A Fundamentals of the Database System B Virtual Manufacturing—A Growing Trend in Automation UNIT 4 A Concepts of Computer Integrated Manufacturing B Enterprise Resources Planning and Beyond Synthetic Applications of Automatic Technology A Recent Advances and Future Trends in Electrical Machine Drivers B System Evolution in Intelligent Buildings PART 6 UNIT 1 UNIT 2 A Industrial Robot B A General Introduction to Pattern Recognition UNIT 3 A Renewable Energy B Electric Vehicles UNIT 1 A

电路 2 电路或电网络由以某种方式连接的电阻器，电感器和电容器等元件组成。如果网络不包含能源，如电池或发电机，那么就被称作无源网络。换句话说，如果存在一个或多个能源，那么组合的结果为有源网络。在研究电网络的特性时，我们感兴趣的是确定电路中的电压和电流。因为网络由无源电路元件组成，所以必须首先定义这些元件的电特性。就电阻来说，电压-电流的关系由欧姆定律给出，欧姆定律指出：电阻两端的电压等于电阻上流过的电流乘以电阻值。在数学上表达为： u=iR (1-1A-1)式中 u=电压，伏特；i =电流，安培；R =电阻，欧姆。纯电感电压由法拉第定律定义，法拉第定律指出：电感两端的电压正比于流过电感的电流随时间的变化率。因此可得到：U=Ldi/dt 式中 di/dt =电流变化率，安培/秒； L =感应系数，享利。电容两端建立的电压正比于电容两极板上积累的电荷 q 。因为电荷的积累可表示为电荷增量 dq 的和或积分，因此得到的等式为 u=，式中电容量 C 是与电压和电荷相关的比例常数。由定义可知，电流等于电荷随时间的变化率，可表示为 i = dq/dt。因此电荷增量 dq 等于电流乘以相应的时间增量，或 dq = i dt，那么等式(1-1A-3)可写为式中 C =电容量，法拉。

PART 1 Electrical and Electronic Engineering Basics UNIT 1 A Electrical Networks B Three-phase Circuits UNIT 2 A The Operational Amplifier ——————————— 5 B Transistors UNIT 3 A Logical Variables and Flip-flop —————————— 8 ———————————— 3 B Binary Number System UNIT 4 A Power Semiconductor Devices —————————— 11 B Power Electronic Converters UNIT 5 A Types of DC Motors —————————————15 B Closed-loop Control of DC Drivers UNIT 6 A AC Machines ———————————————19 B Induction Motor Drive UNIT 7 A Electric Power System ————————————22 B Power System Automation PART 2 Control Theory UNIT 1 A The World of Control ————————————27 B The Transfer Function and the Laplace Transformation UNIT 2 A B —————29 Stability and the Time Response ————————— 30 ————————————— 32 Steady State————————————————— 31 UNIT 3 A The Root Locus B The Frequency Response Methods: Nyquist Diagrams ————— 33 UNIT 4 A The Frequency Response Methods: Bode Piots ————— 34 B Nonlinear Control System 37 UNIT 5 A Introduction to Modern Control Theory B UNIT 6 State Equations 40 38 A Controllability, Observability, and Stability B Optimum Control Systems UNIT 7 A Conventional and Intelligent Control B Artificial Neural Network PART 3 UNIT 1 Computer Control Technology A Computer Structure and Function B 42 43 44 Fundamentals of Computer and Networks UNIT 2 A Interfaces to External Signals and Devices B The Applications of Computers 46 UNIT 3 A PLC Overview B PACs for Industrial Control, the Future of Control 1 UNIT 4 A Fundamentals of Single-chip Microcomputer B Understanding DSP and Its Uses 49 UNIT 5 A A First Look at Embedded Systems B Embedded Systems Design PART 4 UNIT 1 Process Control A A Process Control System 50 B Fundamentals of Process Control 53 52 UNIT 2 A Sensors and Transmitters B Final Control Elements and Controllers UNIT 3 A P Controllers and PI Controllers B PID Controllers and Other Controllers UNIT 4 A Indicating Instruments B Control Panels PART 5 UNIT 1 Control Based on Network and Information A Automation Networking Application Areas B Evolution of Control System Architecture UNIT 2 A Fundamental Issues in Networked Control Systems B Stability of NCSs with Network-induced Delay UNIT 3 A Fundamentals of the Database System B Virtual Manufacturing—A Growing Trend in Automation UNIT 4 A Concepts of Computer Integrated Manufacturing B Enterprise Resources Planning and Beyond PART 6 UNIT 1 Synthetic Applications of Automatic Technology A Recent Advances and Future Trends in Electrical Machine Drivers B System Evolution in Intelligent Buildings UNIT 2 A Industrial Robot B A General Introduction to Pattern Recognition UNIT 3 A Renewable Energy B Electric Vehicles 2 UNIT 1 A

电路 电路或电网络由以某种方式连接的电阻器，电感器和电容器等元件组成。如果网络不包含能源，如电池或发电机，那么就被称作无源网络。换句话说，如果存在一个或多个能源，那么组合的结果为有源网络。在研究电网络的特性时，我们感兴趣的是确定电路中的电压和电流。因为网络由无源电路元件组成，所以必须首先定义这些元件的电特性。就电阻来说，电压-电流的关系由欧姆定律给出，欧姆定律指出：电阻两端的电压等于电阻上流过的电流乘以电阻值。在数学上表达为： u=iR (1-1A-1)式中 u=电压，伏特；i =电流，安培；R =电阻，欧姆。纯电感电压由法拉第定律定义，法拉第定律指出：电感两端的电压正比于流过电感的电流随时间的变化率。因此可得到：U=Ldi/dt 式中 di/dt =电流变化率，安培/秒； L =感应系数，享利。电容两端建立的电压正比于电容两极板上积累的电荷 q 。因为电荷的积累可表示为电荷增量 dq 的和或积分，因此得到的等式为 u=，式中电容量 C 是与电压和电荷相关的比例常数。由定义可知，电流等于电荷随时间的变化率，可表示为 i = dq/dt。因此电荷增量 dq 等于电流乘以相应的时间增量，或 dq = i dt，那么等式(1-1A-3)可写为式中 C =电容量，法拉。

PART 1 Electrical and Electronic Engineering Basics UNIT 1 A UNIT 2 A UNIT 3 A UNIT 4 A UNIT 5 A UNIT 6 A UNIT 7 A Electrical Networks ———————————— 3 B Three-phase Circuits The Operational Amplifier ——————————— 5 Logical Variables and Flip-flop —————————— 8 Power Semiconductor Devices —————————— 11 Types of DC Motors —————————————15 AC Machines ———————————————19 Electric Power System ————————————22 B Transistors B Binary Number System B Power Electronic Converters B Closed-loop Control of DC Drivers B Induction Motor Drive B Power System Automation PART 2 Control Theory UNIT 1 A B UNIT 2 A UNIT 3 A UNIT 4 A The World of Control ————————————27 Stability and the Time Response ————————— 30 The Root Locus ————————————— 32 The Transfer Function and the Laplace Transformation —————29 B Steady State————————————————— 31 B The Frequency Response Methods: Nyquist Diagrams ————— 33 The Frequency Response Methods: Bode Piots ————— 34 B Nonlinear Control System 37 UNIT 5 A Introduction to Modern Control Theory B B B PART 3 B B B State Equations Optimum Control Systems Artificial Neural Network Computer Control Technology 42 43 44 Fundamentals of Computer and Networks The Applications of Computers 46 40 38 UNIT 6 A Controllability, Observability, and Stability UNIT 7 A Conventional and Intelligent Control UNIT 1 A Computer Structure and Function UNIT 2 A Interfaces to External Signals and Devices UNIT 3 A PLC Overview PACs for Industrial Control, the Future of Control 1 UNIT 4 A Fundamentals of Single-chip Microcomputer 49 B B PART 4 B B B B PART 5 B B B B PART 6 Understanding DSP and Its Uses Embedded Systems Design Process Control 50 52 53 Fundamentals of Process Control UNIT 5 A A First Look at Embedded Systems UNIT 1 A A Process Control System UNIT 2 A Sensors and Transmitters Final Control Elements and Controllers PID Controllers and Other Controllers Control Panels Control Based on Network and Information Evolution of Control System Architecture Stability of NCSs with Network-induced Delay Virtual Manufacturing—A Growing Trend in Automation Enterprise Resources Planning and Beyond Synthetic Applications of Automatic Technology UNIT 3 A P Controllers and PI Controllers UNIT 4 A Indicating Instruments UNIT 1 A Automation Networking Application Areas UNIT 2 A Fundamental Issues in Networked Control Systems UNIT 3 A Fundamentals of the Database System UNIT 4 A Concepts of Computer Integrated Manufacturing UNIT 1 A Recent Advances and Future Trends in Electrical Machine Drivers B B B System Evolution in Intelligent Buildings A General Introduction to Pattern Recognition Electric Vehicles UNIT 2 A Industrial Robot UNIT 3 A Renewable Energy 2 UNIT 1 A

电路 电路或电网络由以某种方式连接的电阻器，电感器和电容器等元件组成。如果网络不包含能源，如电池或发电机，那么就被称作无源网络。换句话说，如果存在一个或多个能源，那么组合的结果为有源网络。在研究电网络的特性时，我们感兴趣的是确定电路中的电压和电流。因为网络由无源电路元件组成，所以必须首先定义这些元件的电特性。就电阻来说，电压-电流的关系由欧姆定律给出，欧姆定律指出：电阻两端的电压等于电阻上流过的电流乘以电阻值。在数学上表达为： u=iR (1-1A-1)式中 u=电压，伏特；i =电流，安培；R =电阻，欧姆。纯电感电压由法拉第定律定义，法拉第定律指出：电感两端的电压正比于流过电感的电流随时间的变化率。因此可得到：U=Ldi/dt 式中 di/dt =电流变化率，安培/秒； L =感应系数，享利。电容两端建立的电压正比于电容两极板上积累的电荷 q 。因为电荷的积累可表示为电荷增量 dq 的和或积分，因此得到的等式为 u=，式中电容量 C 是与电压和电荷相关的比例常数。由定义可知，电流等于电荷随时间的变化率，可表示为 i = dq/dt。因此电荷增量 dq 等于电流乘以相应的时间增量，或 dq = i dt，那么等式(1-1A-3)可写为式中 C =电容量，法拉。

Bp network algorithm to achieve a single network, learning neural network with common people.

这是bp网络算法的一个单网实现，对于学习神经网络的人来说常用用。

Bring forward a kind of learning algorithm fitting on the base of spline function, because the spline function has good flexibility and quadratic smoothing property, the search problem of network weight functions training can be converted into the resoluting extreme value problem of the plurality function through using spline function to represent network input and link weight functions, thus the PNN can be trained with the help of the existing neural network learning algorithms;④build a kind of learning algorithm base on the alternate of Walsh function, the complexity of network computing can be decreased through using the complete orthogonality of Walsh function corollary.

应用结果表明该算法收敛速度快，稳定性好；③提出了一种基于样条函数拟和的学习算法，由于样条函数具有很好的柔韧性和二次光滑性，将网络输入函数和连接权函数用样条函数的形式表示，可把网络权函数训练的函数寻优问题转换为多元函数求极值的问题，从而可借助于现有的神经网络学习算法训练过程神经元网络；④建立了一种基于Walsh函数变换的学习算法，利用Walsh函数系的完备正交性，可大大降低网络计算的复杂度。

By taking temperature and horizontal coordinates as network input, and the rib-elevation as network output, the neural network model of rib-elevation was established.

此外，以气温、坐标和横坐标为网络输入，拱肋标高为网络输出，建立了拱肋标高的人工神经网络模型。

The process of establishing neural network is as follows: two-layer neuronic network configuration is selected, S-type active function is used, input parameter of network are selected for thickness, preheat temperature, heat input and sampling point, output parameter of network is selected for fracture toughness property CTOD, learning algorithm of network is used for back-propagation algorithm.

本文选择了2层神经元的神经网络结构，采用S型激活函数，将板厚、预热温度、线能量、取样位置作为神经网络的输入，将环焊接头的裂纹尖端张开位移CTOD值作为网络的输出，通过BP算法的网络学习，采用VC语言建立了X70管线钢环焊接头CTOD与环焊工艺之间的神经网络。

The process of establishing neural network is as follows: input parameters of network are selected from thickness, preheat temperature, heat input, welding position and sampling point, output parameter of network is impact ductility CVN, two-layer neuronic network configuration, S-type active function and back-propagation learning algorithm are selected.

文章摘要：采用VC语言实现了X70管线钢环焊接头冲击韧性与环焊工艺之间神经网络结构的建立过程，将壁厚、预热温度、线能量、焊接位置、取样位置作为结构的输入，将环焊接头的CVN值作为结构的输出，选择了具有2层神经元的神经网络结构和S型激活函数及BP学习算法。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。