DOI: 10.1007/978-3-319-19824-8_20
关键词: Artificial neural network 、 Backpropagation 、 Nervous system network models 、 Algorithm 、 Physical neural network 、 Computer science 、 Types of artificial neural networks 、 Gradient descent 、 Time delay neural network 、 Feedforward neural network
摘要: This paper introduces matrix-valued feedforward neural networks, for which the inputs, outputs, weights and biases are all square matrices. type of networks represents a natural generalization complex-, hyperbolic-, quaternion- Clifford-valued that have been intensively studied over last few years. The full deduction gradient descent algorithm training such is presented. proposed tested on three synthetic function approximation problems, with promising results future.