lstm模型Matlab代码
时间: 2023-08-05 12:02:52 浏览: 49
以下是一个简单的LSTM模型的Matlab代码示例:
```
% 定义LSTM模型参数
input_size = 10; % 输入维度
hidden_size = 20; % 隐藏层维度
output_size = 5; % 输出维度
sequence_length = 30; % 序列长度
learning_rate = 0.01; % 学习率
% 初始化权重和偏置
w_ih = randn(input_size, hidden_size) * 0.01;
w_hh = randn(hidden_size, hidden_size) * 0.01;
w_ho = randn(hidden_size, output_size) * 0.01;
b_ih = zeros(1, hidden_size);
b_ho = zeros(1, output_size);
% 初始化状态
h = zeros(1, hidden_size);
c = zeros(1, hidden_size);
% 准备数据
inputs = randn(sequence_length, input_size);
targets = randn(sequence_length, output_size);
% 前向传播
for t = 1:sequence_length
x = inputs(t,:);
a = x * w_ih + h * w_hh + b_ih;
i = sigmoid(a(1:hidden_size));
f = sigmoid(a(hidden_size+1:2*hidden_size));
o = sigmoid(a(2*hidden_size+1:3*hidden_size));
g = tanh(a(3*hidden_size+1:end));
c = f .* c + i .* g;
h = o .* tanh(c);
y = h * w_ho + b_ho;
loss = sum((y - targets(t,:)).^2);
% 反向传播
dy = 2 * (y - targets(t,:));
dw_ho = h' * dy;
db_ho = dy;
dh = dy * w_ho';
do = dh .* tanh(c);
dc = dh .* o .* (1 - tanh(c).^2);
dc = dc + c .* (f' - 1);
df = dc .* c;
di = dc .* g;
dg = dc .* i;
da = [di .* i .* (1 - i), df .* f .* (1 - f), do .* o .* (1 - o), dg .* (1 - g.^2)];
dw_ih = x' * da;
dw_hh = h' * da;
db_ih = sum(da);
% 更新参数
w_ih = w_ih - learning_rate * dw_ih;
w_hh = w_hh - learning_rate * dw_hh;
w_ho = w_ho - learning_rate * dw_ho;
b_ih = b_ih - learning_rate * db_ih;
b_ho = b_ho - learning_rate * db_ho;
end
```
这是一个基本的LSTM模型代码示例,实现了前向传播和反向传播。你可以根据你的实际需求进行修改和扩展。