Input ranges:输入的范围,如Get from input p,由下拉式选单选取。 Training function:训练函数,如TRAINLM(LM算法)。 Adaption learning function:适应性学习函数,如LEARNGDM(具动量的梯度下降法) Performance function:性能函数,如MSE(均方误差)。 Number of layers:隐藏层的层数,如 2。 Properties for:由下拉式选单...
Input ranges:輸入的範圍,如Get from input p,由下拉式選單選取。 Training function:訓練函數,如TRAINLM(LM演算法)。 Adaption learning function:適應性學習函數,如LEARNGDM(具動量的梯度下降法) Performance function:性能函數,如MSE(均方誤差)。 Number of layers:隱藏層的層數,如 2。 Properties for:由下拉式選...
Properties for:由下拉式选单选取欲进行设定的隐藏层,如Layer 1 。Number of neurons :隐藏层1中神经元的数目,女口15。Transfer function :隐藏层1所使用的转移函数类型,如TANSIG图6?建立网络的窗口,目前动作为设定隐藏层1的性质2的性质图8?网络建立完成后会在 Networks栏框中出现建立的网络名称vstep.4网络初始...
matlabsimulink教程1 - 汽车试验与故障诊断.docx,untitled窗口,如图7.2所示。 untitled窗口,如图7.2所示。(5)用同样的方法打开接收模块库“Sinks”,选择其中的“S .11续】设置各模块的属性,建立一个与【例7.3】模型参数相同的二阶系统模型。则系统模型框图如图7. 的基础
The functionsys = tf(numerator,denominator)generates a continuous time transfer function model by considering the numerator as well as denominator properties. The functionsys = tf(numerator,denominator,ts)generates a discrete-time transfer function model by considering the numerator as well as denominator...
2. State-space model from a transfer function The SS representation of a given system can be determined from its frequency response on rational form. Basically, there are three different rational forms (models) that can represent a measured or calculated frequency response: pole-zero form, polynom...
classdef DebugDemo properties PublicProp = 0 end properties (Access=private) PrivateProp = 0 end methods function obj = incPrivateProp(obj) obj.PrivateProp = obj.PrivateProp + 1; end end end 构造DebugDemo 类的实例 test,然后调用 incPrivateProp 方法。 test = DebugDemo; test.incPrivateProp ...
Describe the properties of the Laplace transform. Apply Laplace transforms to solve initial value problems. Recall the definition of a linear time-invariant (LTI) operator. TransferFunctionBasics.mlx Derive transfer functions by hand. Derive transfer functions using symbolic math. ...
46、性(Properties for ):Layer1 神经元个数(Number of neurons):5; 传输函数(Transfer Function):LOGSIG;Layer2 Number of neurons:1; Transfer Function:LOGSIG;图9.26创建神经网络窗口 单击View按钮可以查看定义好的网络,如图9.27所示;图9.27 定义的神经网络结构图图9.28 设定数据视图窗口 单击Create按钮,关闭本窗...
TransferStatus = idle Type = serial UserData = [] ValuesReceived = 0 ValuesSent = 0 SERIAL specific properties: BaudRate = 9600 BreakInterruptFcn = DataBits = 8 DataTerminalReady = on FlowControl = none Parity = none PinStatus = [1x1 struct] ...