KFUPM Control & Instrumentation Engineering Club’s Post

MATLAB is one of the software platforms most widely used for scientific computation. MATLAB includes a large set of functions, packages, and toolboxes, making it simple and fast to obtain complex mathematical and statistical computations for many applications. In this chapter, Juan Ruiz de Miras reviews some tools available in MATLAB for performing fractal analyses on typical neuroscientific data in a practical way, providing detailed examples of how to calculate the fractal dimension of 1D, 2D, and 3D data in MATLAB and other software as well. https://lnkd.in/g_smsJ2n

I really found this course very informative that I wish I could have taken this course before I took a graduate-level course on numerical methods. I had a good refresher here on root finding and I had a glimpse how to easily solve nonlinear equations in MATLAB (and it is really easy to do so!). I also liked the featured projects, especially the last one about the population dynamics of cheetahs and lions. The featured project showed the practicality of solving nonlinear equations. I'm looking forward now to solve more nonlinear problems (on any field).

Building a Face Recognition Script on MATLAB (Step by Step) Creating a Face ID system using MATLAB was a challenging yet rewarding experience. From fine-tuning face detection to extracting and comparing unique features, each step presented its own set of obstacles. One of the biggest challenges was ensuring reliable face detection under different conditions, but persistence paid off. Now, our focus is on integrating this system into more practical applications. Curious about the details? Read the full story on Medium, and what's next for this project.

Wow, thrilled about the native support for SUNDIALS suite of solvers in MATLAB. Some fifteen years ago in my first paper as a graduate student, the sensitivity analysis functionality in the CVODES solver allowed us to demonstrate formal reachability analysis on Simulink model in Alexandre Donzé's Breach tool, but the plumbing to enable that was nontrivial (see the Figure screenshot, link to the paper in the comments). Now with the native support, it's as easy as replacing d.Solver = 'ode45' with d.Solver = "cvodesnonstiff". Check out the blog post and play with the script in MATLAB Online. https://lnkd.in/eTFcK9Qr

Introduction to Fuzzy Logic using MATLAB Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference. Buy: https://amzn.to/4dSUiua PDF: https://lnkd.in/dEZhC8S9

Analysis and Simulation of Signal and Systems is a new book issued recently. It is a text and practice book with several MATLAB examples. Dr. Zeinali and I try to collect our experiences in this book for students.

𝙑𝙖𝙧𝙞𝙤𝙪𝙨 𝙏𝙚𝙘𝙝𝙣𝙞𝙦𝙪𝙚𝙨 𝙤𝙛 𝙁𝙞𝙣𝙙𝙞𝙣𝙜 𝘿𝙁𝙏: 𝘼 𝙍𝙚𝙥𝙤𝙧𝙩 📊 Report Overview: 1️⃣ Optimized 8-point Decimation in Time FFT Butterfly Diagram: Minimized twiddle factors, calculated complex multiplications and additions.   2️⃣ Calculation of 8-point DFT of x[n]: Step-by-step solution provided.   3️⃣ MATLAB Scripts: Developed for efficient FFT calculations, compared with MATLAB's functions.   4️⃣ Cooley-Tukey FFT Algorithm: Implemented for 15-point FFT, compared with MATLAB's commands. 🔬 Key Findings: - Optimized FFT techniques explored, scripts developed and compared with MATLAB. - Performance of custom scripts evaluated against standard library functions. 📈 Takeaways: - Understanding of FFT optimization and implementation in MATLAB. - Comparison between custom and standard FFT implementations for accuracy and efficiency. #DFT #DigitalSignalProcessing #FFT #MATLAB

👉What is Interpretability in machine learning? Learn how interpretability helps reveal how machine learning models make predictions, why interpretability is important, and how to apply interpretability techniques with MATLAB. #machinelearning #matlab

👉What is Interpretability in machine learning? Learn how interpretability helps reveal how machine learning models make predictions, why interpretability is important, and how to apply interpretability techniques with MATLAB. #machinelearning #matlab

👉What is Interpretability in machine learning? Learn how interpretability helps reveal how machine learning models make predictions, why interpretability is important, and how to apply interpretability techniques with MATLAB. #machinelearning #matlab