Table of Contents I. Introduction 2. Feature decomposition 3. Image compression based on SVD 4. Feature dimensionality reduction based on SVD 1. Foreword In fact, EVD (eigendecomposition) is a special case of SVD; inverse is a special case of pseudo-inverse, which has applications in least squares. There will be SVD decomposition in the “8-point method” […]
Tag: pca
Principal component analysis PCA is PC1 or PC1 + PC2
I saw that PCA=∑ (PC1 + PC2) is used in the literature, and there are also values describing the PCA score. How should the PCA score be calculated? . . . . . . A review of the steps for PCA: 1. Determine the number of principal components 2. Extract principal components 3. Principal component […]
Principal component analysis (PCA) and wine data set example code
1. Main steps of principal component analysis Principal component analysis (PCA) is an unsupervised linear transformation technique that is widely used in different fields, especially feature extraction and dimensionality reduction. His application areas include exploratory data analysis and denoising for stock market trading, and genomic data and gene expression level analysis in bioinformatics. PCA helps […]
PCA9865 module usage
It is originally used to control lights. If it is used to control servos, etc., an external power supply is required. arduino arduino stm32 Pin A4 is SDA and pin A5 is SCL asrpro Use softiic library and use arduino’s Adafruit_PWMServoDriver driver library to modify To encapsulate, you need to copy the contents of the […]
18.3 NPCAP builds man-in-the-middle attack
ARP spoofing is a network attack method that aims to deceive the target host to achieve network attacks. The ARP protocol is a protocol used to obtain MAC addresses, so spoofers can use ARP spoofing to force their target hosts to send network traffic to attacker-controlled devices, thereby achieving network attacks. ARP spoofing attacks usually […]
18.3 NPCAP custom packet filtering
The NPCAP library is a library for network packet capture and analysis on Windows platforms. It is a fork of the WinPcap library, developed by the Nmap development team and used in the Nmap software. Like WinPcap, the NPCAP library provides APIs that allow developers to easily capture and process network packets in their applications. […]
Zero-copy mmap of libpcap
1. User space After creating fd through socket(AF_PACKET,…), establish the receiving queue //pcap-linux.c static int pcap_activate_linux(pcap_t *handle) {<!– –> … ret = setup_mmapped(handle, & amp;status); … } 1.1 Set the default ring bufer size static int setup_mmapped(pcap_t *handle, int *status) {<!– –> … \t//1. if (handle->opt.buffer_size == 0) {<!– –> /* by default request 2M […]
[BP Regression Prediction] Based on principal component analysis combined with BP neural network PCA-BP heating furnace temperature prediction with Matlab code…
?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For cooperation on MATLAB projects, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more complete Matlab code and simulation customization content, click Intelligent optimization algorithm […]
[BP Regression Prediction] Based on principal component analysis combined with BP neural network PCA-BP heating furnace temperature prediction with Matlab code
?About the author: A Matlab simulation developer who loves scientific research. He cultivates his mind and improves his technology simultaneously. For cooperation on MATLAB projects, please send a private message. Personal homepage: Matlab Research Studio Personal credo: Investigate things to gain knowledge. For more Matlab complete code and simulation customization content, click Intelligent optimization algorithm […]
[Text Feature Representation (4)] Embedding is applied in clustering systems, using PCA for dimensionality reduction
What is clustering Clustering means clustering samples that are close to each other. The essence is to use a representation and similarity measure to process text. For example, we have a large amount of unclassified text. If we can know how many categories there are in advance, we can use the clustering method to roughly […]