Thriving in an exponential world requires more than a better strategy. It demands quantum thinking, the shift from linear ...

Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...

This project implements a 2-layer RBF network that learns to approximate the target function f(p) = sin(p) for p ∈ [0, π]. The network uses Gaussian activation functions in the hidden layer and linear ...

Abstract: Block cipher is used as an important technology to protect data confidentiality and user privacy in many fields such as machine learning and cloud storage. Vectorial Boolean functions often ...