卷积神经网络分类算法是一种近年来应用广泛的高效识别算法，在模式识别、

Convolutional neural network classification algorithm is a highly efficient recognition algorithm that has been widely used in recent years. It has played a significant role in pattern recognition and image processing. It has the characteristics of simple structure, strong adaptability and few training parameters. This article will start from the development history of convolutional neural networks, and elaborate the mathematical principles, neuron models and training algorithms of convolutional neural networks at different levels.

Convolution neural network classification algorithm is a kind of high-efficiency recognition algorithm widely used in recent years, which plays a significant role in pattern recognition, image processing and other fields. This paper will begin with the development history of convolutional neural networks, and expound the mathematical principles, neuron models and training algorithms of convolutional neural networks at different levels.

Convolutional neural network classification algorithm is an efficient recognition algorithm widely used in recent years. It has played a significant role in pattern recognition, image processing and other fields. It has the characteristics of simple structure, strong adaptability and less training parameters. Starting from the development history of convolutional neural network, this paper expounds the mathematical principles, neural models and training algorithms of different levels of convolutional neural network.<br>