用matlab写gru
时间: 2023-10-31 07:14:47 浏览: 31
这里是一个简单的GRU网络的Matlab代码示例:
```
% 输入矩阵大小:numFeatures x numInputs
% 输出矩阵大小:numOutputs x numInputs
% 隐藏状态矩阵大小:numHiddenUnits x numInputs
numInputs = 10; % 输入序列长度
numHiddenUnits = 20; % 隐藏状态向量长度
numOutputs = 5; % 输出序列长度
numFeatures = 15; % 特征向量长度
% 初始化参数
Wz = randn(numHiddenUnits, numFeatures);
Wr = randn(numHiddenUnits, numFeatures);
Wh = randn(numHiddenUnits, numFeatures);
Uz = randn(numHiddenUnits, numHiddenUnits);
Ur = randn(numHiddenUnits, numHiddenUnits);
Uh = randn(numHiddenUnits, numHiddenUnits);
bz = randn(numHiddenUnits, 1);
br = randn(numHiddenUnits, 1);
bh = randn(numHiddenUnits, 1);
Wy = randn(numOutputs, numHiddenUnits);
by = randn(numOutputs, 1);
% 初始化隐藏状态
h = zeros(numHiddenUnits, 1);
% 循环处理输入序列
for t = 1:numInputs
% 读取输入向量
x = randn(numFeatures, 1);
% 计算重置门r和更新门z
r = sigmoid(Wr * x + Ur * h + br);
z = sigmoid(Wz * x + Uz * h + bz);
% 计算临时隐藏状态h_tilde
h_tilde = tanh(Wh * x + Uh * (r .* h) + bh);
% 更新隐藏状态h
h = (1 - z) .* h + z .* h_tilde;
end
% 计算输出序列
outputs = zeros(numOutputs, numInputs);
for t = 1:numInputs
% 读取输入向量
x = randn(numFeatures, 1);
% 计算重置门r和更新门z
r = sigmoid(Wr * x + Ur * h + br);
z = sigmoid(Wz * x + Uz * h + bz);
% 计算临时隐藏状态h_tilde
h_tilde = tanh(Wh * x + Uh * (r .* h) + bh);
% 计算输出向量y
y = softmax(Wy * h + by);
outputs(:, t) = y;
% 更新隐藏状态h
h = (1 - z) .* h + z .* h_tilde;
end
```
其中sigmoid和softmax函数的实现如下:
```
function y = sigmoid(x)
y = 1 ./ (1 + exp(-x));
end
function y = softmax(x)
ex = exp(x);
y = ex ./ sum(ex);
end
```