---

def tanh(x):
    return np.tanh(x)

def relu(x):
    return np.maximum(0, x)

class AlternativeNeuron:
    def __init__(self, weights, bias, activation_func):
        self.weights = weights
        self.bias = bias
        self.activation = activation_func

    def feedforward(self, inputs):
        total = np.dot(self.weights, inputs) + self.bias
        return self.activation(total)

# Пример использования ReLU
neuron_relu = AlternativeNeuron(np.array([0.5, 0.5]), 0, relu)
print(f"ReLU Neuron Output: {neuron_relu.feedforward(np.array([1, -2]))}")