[prediction model] optimize BP neural network based on longicorn whisker algorithm to realize data prediction matlab source code

1 Introduction to algorithm 1.1 principle of BP neural network algorithm affected by relevant indexes As shown in Figure 1, when training BP using MATLAB's newff function, it can be seen that most cases are three-layer neural networks (i.e. input layer, hidden layer and output layer). Here to help understand the principle of neural network: 1 ...

Posted by tzzoug on Sat, 18 Sep 2021 19:52:24 -0700

Brian2_ Impulse neural network_ Neuron learning record

Impulse neural network is called the third generation neural network, which has higher biological reliability. SNN has always occupied the core position in the research of brain like science in recent years. When the performance is similar, the chip based on pulse neural network has lower power consumption, better stability and robustness than ...

Posted by coverman on Thu, 16 Sep 2021 11:38:05 -0700

Improving BP network to realize data prediction based on Harris Eagle algorithm

Introduction of BP network prediction algorithm 1. Introduction to Artificial Neural Network Artificial Neural Network (ANN) is a computer system formed by several very simple processing units connected to each other in some way to mimic the structure and function of the human brain. It processes information by the dynamic response of its sta ...

Posted by Jim_Bo on Tue, 14 Sep 2021 09:13:02 -0700

Recognition of fashion MNIST data set by convolutional neural network (DenseNet) (pytoch version)

1. Preface 1.1 case introduction In this case, pytoch is used to build a DenseNet network structure for image classification of fashion MNIST dataset. The analysis of this problem can be divided into data preparation, model establishment, training with training set and testing the effect of model with test set. 1.2 environment configurat ...

Posted by OhLordy on Fri, 10 Sep 2021 01:45:07 -0700

Fundamentals of machine learning and neural networks, pytoch framework

Fundamentals of machine learning The essence of machine learning: using data to solve problems Data preprocessing (important in deep learning) - > training phase - > model generation - > prediction phase We usually choose some data as the test set, such as about 20%. Sometimes there is an additional verification set of about 20 ...

Posted by hyngvesson on Wed, 08 Sep 2021 00:38:35 -0700