格雷格·希思
Backgound in Electromagnetic Theory, Plasma Physics and Radar Target Identification using Neural Networks.
PhD Student, Research Assistant and Lecturer at Stanford;
AB,SCB,SCM学生;布朗研究助理,研究员和教授;
27 yrs researching Ballistic and Theatre Missile Defense using Neural Networks at MIT Lincoln Laboratory. Retired 2003.
PLEASE DO NOT SEND QUESTIONS AND DATA TO MY EMAIL. HOWEVER, CAN SEND LINKS TO POSTS.
Professional Interests: Neural Netwoks, Spectral Analysis
Statistics
MATLAB Answers
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Would this be considered underfitting?
A model is UNDERFIT if and only if No. of independent training equations < No. of unknowns Hope this helps Tha...
Would this be considered underfitting?
A model is UNDERFIT if and only if No. of independent training equations < No. of unknowns Hope this helps Tha...
1년| |0
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Avoid exploding/vanishing gradient problem with NARX nets?
使用较高的开环的同性恋目标。然后在循环关闭后降低值。自从我这样做已经好几年了...
Avoid exploding/vanishing gradient problem with NARX nets?
使用较高的开环的同性恋目标。然后在循环关闭后降低值。自从我这样做已经好几年了...
2년| |0
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How to make prediction from a trained NARX neural network?
You forgot to include the intial conditions: yz = nets(xz,xiz,aiz); Thank you for formally accepting my answer Greg
How to make prediction from a trained NARX neural network?
You forgot to include the intial conditions: yz = nets(xz,xiz,aiz); Thank you for formally accepting my answer Greg
2년| |0
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在训练神经网络(NN)时退出记忆问题,阵列超出了使用BackPropjacobianstatic的最大数组大小的偏好
A single hidden layer is sufficient. Hope this helps Thank you for formally accepting my answer Greg
在训练神经网络(NN)时退出记忆问题,阵列超出了使用BackPropjacobianstatic的最大数组大小的偏好
A single hidden layer is sufficient. Hope this helps Thank you for formally accepting my answer Greg
2년| |0
답변 있음
在训练神经网络(NN)时退出记忆问题,阵列超出了使用BackPropjacobianstatic的最大数组大小的偏好
A single hidden layer is sufficient. Hope this helps Thank you for formally accepting my answer Greg
在训练神经网络(NN)时退出记忆问题,阵列超出了使用BackPropjacobianstatic的最大数组大小的偏好
A single hidden layer is sufficient. Hope this helps Thank you for formally accepting my answer Greg
2년| |0
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Difference between function of sim and predict in Neural network?
help sim doc sim help predict doc predict Thank you for formally accepting my answer Greg
Difference between function of sim and predict in Neural network?
help sim doc sim help predict doc predict Thank you for formally accepting my answer Greg
2년| |0
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Forecasting using GRNN (Generalized Regression Neural Network)?
是的,将输入数据和输出数据标准化为[-1,1]。最小化足够多项式拟合的顺序。最小化...的数量
Forecasting using GRNN (Generalized Regression Neural Network)?
是的,将输入数据和输出数据标准化为[-1,1]。最小化足够多项式拟合的顺序。最小化...的数量
2년| |0
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CNN With unbalanced Data
Although you do not prefer data augmentation, duplication of the smaller dataset examples is probably the quickest and most reli...
CNN With unbalanced Data
Although you do not prefer data augmentation, duplication of the smaller dataset examples is probably the quickest and most reli...
2년| |0
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Trained neural network to optimize input variable
"OPTIMIZED INPUT" is ill-defined Just train another net x2 = f2(x1,y1,y2) Hope this helps, THANK YOU FOR FORMALLY ACCEP...
Trained neural network to optimize input variable
"OPTIMIZED INPUT" is ill-defined Just train another net x2 = f2(x1,y1,y2) Hope this helps, THANK YOU FOR FORMALLY ACCEP...
약22 |0
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Training data and Training target in Neural Networks
You cannot make any intelligent decisions until you have examined a plot of the data!!! (WRONG!!! Plotting the data first is ...
Training data and Training target in Neural Networks
You cannot make any intelligent decisions until you have examined a plot of the data!!! (WRONG!!! Plotting the data first is ...
2년| |0
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How to avoid getting negative values when training a neural network?
在输出层中使用Sigmoid。希望这有助于您正式接受我的答案Greg
How to avoid getting negative values when training a neural network?
在输出层中使用Sigmoid。希望这有助于您正式接受我的答案Greg
2년| |0
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weird plotregression plots for a 10% of my fitnet neural networks
有时培训进入参数空间车辙。这就是为什么训练多个型号是明智的。希望这可以帮助。格雷格...
weird plotregression plots for a 10% of my fitnet neural networks
有时培训进入参数空间车辙。这就是为什么训练多个型号是明智的。希望这可以帮助。格雷格...
2년| |0
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What is the purpose of shuffling the validation set?
To impose and verify a consistent GENERALIZED path to convergence by avoiding repetitive anomalies. Hope this helps Greg
What is the purpose of shuffling the validation set?
To impose and verify a consistent GENERALIZED path to convergence by avoiding repetitive anomalies. Hope this helps Greg
2년| |0
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How to force overfiting of Deep Learning Network for Classification
与训练向量相比,过度拟合=更多的训练未知数(例如,权重)。过度训练1 =训练一个过度拟合网络到...
How to force overfiting of Deep Learning Network for Classification
与训练向量相比,过度拟合=更多的训练未知数(例如,权重)。过度训练1 =训练一个过度拟合网络到...
2년| |0
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Neural Network Pattern Recognition
Targets are 1-dimensional unit vectors with 4 zeros and a single 1 . Thank you for formally accepting my answer. Greg
Neural Network Pattern Recognition
Targets are 1-dimensional unit vectors with 4 zeros and a single 1 . Thank you for formally accepting my answer. Greg
2년| |0
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重复推断时,词质表演产生略有不同的值
Use clear all, close all, clc, rng(0) on the 1st line Thank you for formally accepting my answer Greg
重复推断时,词质表演产生略有不同的值
Use clear all, close all, clc, rng(0) on the 1st line Thank you for formally accepting my answer Greg
2년| |0
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combining two neural networks (net1 is trained & net2 is untrained) in one bigger network
只有1.将net1的输出保存在文件中2.使用文件来训练net2 greg
combining two neural networks (net1 is trained & net2 is untrained) in one bigger network
只有1.将net1的输出保存在文件中2.使用文件来训练net2 greg
2년| |0
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Problem with the TreeBagger Command
输入功能和输出目标的大小必须为[i n] = size(输入)[o n] = size(target)希望这有帮助...
Problem with the TreeBagger Command
输入功能和输出目标的大小必须为[i n] = size(输入)[o n] = size(target)希望这有帮助...
2년| |0
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how to augment image data only for a specific class?
Separate class 0 and interpolate. If you have a good feel for the data you could extrapolate. However the latter might be tricky...
how to augment image data only for a specific class?
Separate class 0 and interpolate. If you have a good feel for the data you could extrapolate. However the latter might be tricky...
2년| |0
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NTSTOOL - How to get predicted values of "the future"?
The known time series is analyzed to yield a time-series model that uses past and present values to predict future values. The ...
NTSTOOL - How to get predicted values of "the future"?
The known time series is analyzed to yield a time-series model that uses past and present values to predict future values. The ...
2년| |0
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timedelaynet输出计算原理
You did not include tHe 2 biases. Hope this helps. Greg THANK YOU FOR FORMALLY ACCEPTING MY ANSWER
timedelaynet输出计算原理
You did not include tHe 2 biases. Hope this helps. Greg THANK YOU FOR FORMALLY ACCEPTING MY ANSWER
2년| |0