bp神经网络matlab程序

以下是一个基本的BP神经网络的MATLAB程序：

%% 准备数据
data = [0 0; 0 1; 1 0; 1 1]; % 输入数据
target = [0; 1; 1; 0]; % 目标输出

%% 设定神经网络参数
hidden_layer_size = 4; % 隐藏层神经元数量
learning_rate = 0.1; % 学习率
max_iterations = 10000; % 最大迭代次数

%% 初始化权值和偏置
input_layer_size = size(data, 2);
output_layer_size = size(target, 2);
W1 = rand(input_layer_size, hidden_layer_size) - 0.5;
b1 = rand(1, hidden_layer_size) - 0.5;
W2 = rand(hidden_layer_size, output_layer_size) - 0.5;
b2 = rand(1, output_layer_size) - 0.5;

%% 训练神经网络
for i = 1:max_iterations
% 前向传播
hidden_layer_activation = tanh(data * W1 + b1);
output = tanh(hidden_layer_activation * W2 + b2);

% 计算误差和损失
error = target - output;
loss = sum(error .^ 2) / size(data, 1);

% 反向传播
output_delta = error .* (1 - output .^ 2);
hidden_layer_delta = (output_delta * W2') .* (1 - hidden_layer_activation .^ 2);

% 更新权值和偏置
W2 = W2 + learning_rate * hidden_layer_activation' * output_delta;
b2 = b2 + learning_rate * sum(output_delta);
W1 = W1 + learning_rate * data' * hidden_layer_delta;
b1 = b1 + learning_rate * sum(hidden_layer_delta);

% 检查是否达到停止条件
if loss < 1e-6
break;
end
end

%% 使用训练好的网络进行预测
prediction = tanh(tanh(data * W1 + b1) * W2 + b2);
disp(prediction);