❇️General Fuzzy C-Means Clustering with Objective Function Control
In this MATLAB tutorial, we explore the General Fuzzy C-Means (GFCM) clustering strategy, a novel approach from the IEEE Transactions on Fuzzy Systems that enhances the traditional fuzzy C-means clustering by using an objective function to control fuzziness. This method improves clustering precision by providing a clear definition of fuzzy degree, enabling exact control over results. We demonstrate the GFCM algorithm's adaptability across various distance metrics and fuzzy degrees, emphasizing the importance of choosing the right fuzzy degree. The tutorial covers theoretical basics, practical applications, and the algorithm’s convergence and stability, offering valuable insights for students, researchers, and professionals in data science and machine learning.
🔻YouTube: https://youtu.be/o9DxlIYMNM0
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#FuzzyClustering #DataScience #MachineLearning #IEEE #FuzzySystems #Clustering #ObjectiveFunction #GFCM

Reinforcement Learning Toolbox™
User's Guide 2023a

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#Reinforcement_Learning #Toolbox #RL #2023a #Environments #Designer #Simulink #Agents #Q_Learning #SARSA #Deep_Q_Network #Policy #Actor #Deep_Deterministic_Policy_Gradient #TD3 #PPO #TRPO #MBPO #NN

نکاتی در مورد متلب 2023a
دارک مود ، نحوه دانلود و نصب ، برخی مزایا و معایب
نحوه دانلود و نصب کتابخانه و مثال های اماده از داخل متلب
نحوه استفاده از راهنما و مثال های آماده
اجرای مثال اماده یادگیری تقویتی پارک اتوماتیک
اجرای مثالی از طراحی اپ
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❇️Track Multiple Vehicles Using a Camera❇️
This example shows how to detect and track multiple vehicles with a monocular camera mounted in a vehicle.

✅Overview
Automated Driving Toolbox™ provides pretrained vehicle detectors and a multi-object tracker to facilitate tracking vehicles around the ego vehicle. The vehicle detectors are based on ACF features and Faster R-CNN, a deep-learning-based object detection technique. The detectors can be easily interchanged to see their effect on vehicle tracking.

The tracking workflow consists of the following steps:

Define camera intrinsics and camera mounting position.

Load and configure a pretrained vehicle detector.

Set up a multi-object tracker.

Run the detector for each video frame.

Update the tracker with detection results.

Display the tracking results in a video.
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#Track #Vehicles #Camera #detector #intrinsics #Driving_Toolbox #R_CNN #deep_learning #ACF

Automated Driving Toolbox™
User’s Guide 2023a

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#Sensor #Vehicle #Pattern #Camera #Estimation #Labelling #App #Moving #Drawing #Automated #Simulation #Kalman_Filters #Map #Control #Velocity #NCAP #3D

✅Guidance and Navigation of Aircraft using Model Predictive Control

❇️FlightGear V3
❇️Simulink
❇️just run

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#AircraftNavigation #FlightControl #ModelPredictiveControl #FlightGearV3 #Simulink #AviationTechnology #AircraftGuidance #FlightSimulation #AerospaceEngineering #AircraftAutomation #AviationSimulation #FlightTraining #AutonomousFlight #FlightSimulationSoftware #AircraftSystems #AircraftDevelopment #AircraftTechnology #FlightGearCommunity #SimulinkModeling #AerospaceInnovation

تحلیل و طراحی کنترل موقعیت ربات یک درجه آزادی با استفاده از منطق فازی (تولباکس) در متلب

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❇️"Designing Fuzzy Systems with Recursive Least Squares | MATLAB Simulink Tutorial for Cruise Control and DC Motor Speed"❇️

more in coment

To watch in
🔻YouTube: https://youtu.be/v8HKEJELShA
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#FuzzyLogic #MATLABSimulink #ControlSystems #RecursiveLeastSquares #GaussianFunctions #SystemTesting #OptimalControl #AdaptiveControl #TechTutorial #Engineering #MATLABCoding #RealTimeControl #AlgorithmExplanation #VersatileSystems #OnlineLearning

❇️Transfer Function Coefficient Identification with MATLAB: Markov Series and Hankel Matrix Method

Description:

"Dive into MATLAB as we explore the Markov series and Hankel matrix method for identifying transfer function coefficients. This tutorial guides you through the step-by-step process of extracting numerator and denominator coefficients, shedding light on the intricacies of system identification. Perfect for engineers and enthusiasts looking to enhance their understanding of transfer function modeling.
To watch in
🔻YouTube: https://youtu.be/tuHf-3MOGiM
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#MATLAB #TransferFunction #SystemIdentification #ControlSystems #Engineering #MarkovSeries #HankelMatrix #MATLABCoding #CoefficientIdentification

❇️پروژه درس شناسایی سیستم

—شناسایی سیستم به صورت فضای حالت
—شناسایی سیستم با مدل های ARX , OE , BJ
—شناسایی غیر خطی NLARX ,...
—شناسایی جعبه خاکستری
—بهبود مدل با استفاده از همرشناین وینر
—شناسایی حوزه زمان سیستم با تولباکس شناسایی سیسیتم
—طراحی کنترل کننده پیش بین برای مدل شناسایی شده
—مقایسه کنترل کننده پیش بین با کنترل کننده PID همراه با نویز در خروجی و ورودی سیستم و ردیابی ورودی مرجع
—راهکاری ساده برای فیلتر نویز و...
دانلود:
https://npd.servr.ir/ident/pro/


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#MATLABCoding #ControlSystems #SystemIdentification #Modeling #NonlinearIdentification #PredictiveControl #PIDController #NoiseFiltering #Simulation #MATLABTutorial

❇️Revolutionizing Multi-Robot Path Planning: Adaptive Differential Sine-Cosine Algorithm

In this video, we explore the innovative Multi-Strategy and Self-Adaptive Differential Sine–Cosine Algorithm in MATLAB, enhancing multi-robot path planning. Surpassing the traditional SCA, this approach introduces diverse strategies for better adaptability and performance, achieving a 42% improvement in navigating complex environments. Discover its application, comparisons with leading algorithms, and its potential to transform robotics.
🔻YouTube: https://youtu.be/4ZSgFP-G-jY
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#Robotics #PathPlanning #MATLABSimulation #AlgorithmImprovement #MultiRobotSystems #AdaptiveAlgorithms #SineCosineAlgorithm #MetaheuristicAlgorithms #EngineeringInnovation #TechExploration

❇️Mastering Optimization with Slime Mould Algorithm: A MATLAB Tutorial
Dive into our MATLAB tutorial on the Slime Mould Algorithm (SMA) for stochastic optimization. Learn how SMA, inspired by nature, addresses complex optimization problems. This video covers SMA's basics, its MATLAB implementation, and showcases its effectiveness with visualizations and examples, catering to both beginners and experts. Ideal for researchers, students, and enthusiasts in computational intelligence, this tutorial is designed to enrich your optimization knowledge and spark innovation.
🔻YouTube: https://youtu.be/FqDkJSRGBiU
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#SlimeMouldAlgorithm #OptimizationTutorial #MATLABCoding #StochasticOptimization #AlgorithmVisualisation #ComputationalIntelligence #MATLABTutorial #EngineeringEducation #ScienceAndTechnology #ResearchInnovation

❇️Bacterial Foraging Optimization (BSO) ❇️

The text describes a 2D optimization problem aiming to minimize the distance between a position (x1, x2) and the target point (1, 2), with the optimal solution being (1, 2) where the fitness value is zero. It introduces the Bacterial Swarm Optimization (BSO) algorithm, a heuristic method inspired by bacterial foraging behavior. The algorithm operates through a population of individuals that navigate the search space to find the optimal solution based on fitness values and probabilistic rules. It adapts step size and swim length for a balance between exploration and exploitation, and uses elimination-dispersal events to avoid local optima. The algorithm's effectiveness depends on parameter selection and the problem's nature.
🔻YouTube: https://youtu.be/XvQw0RALeTo
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#BSO #algorithm #heuristic #optimization #search_space #bacteria #population #exploration #exploitation
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🟢R2024a Release Highlights🟢
#MATLAB

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❇️Major Updates:
- Computer Vision Toolbox: Deploy YOLOX object detection; conduct team-based labeling; perform real-time visual SLAM.
- Deep Learning Toolbox: Support architectures such as transformers; import and co-simulate PyTorch and TensorFlow models.
- GPU Coder: Generate generic CUDA for deep learning; use single memory manager and profile code for MEX code generation.
- Instrument Control Toolbox: Use the Instrument Explorer app to manage devices with IVI and VXIplug&play drivers without writing code.
- Satellite Communications Toolbox: Model multiplatform scenarios and perform visibility and communications link analyses on them.
- UAV Toolbox: Design and deploy flight controller for a vertical take-off and landing (VTOL) UAV with PX4 hardware-in-the-loop simulation; interface with PX4 Cube Orange Plus and Pixhawk 6c autopilots.

❇️Transitions:
- Simulink 3D Animation: Simulate and visualize dynamic systems in Unreal Engine 5.1 with new prebuilt scenes, actors, and sensors.
- SoC Blockset: Prototype and test on SDR and vision hardware with SoC Blockset Support Package for Xilinx Devices.

❇️MATLAB and Simulink Updates:
- Editor Spell Checker: Check spelling in text and comments in MATLAB code files.
- Simulink Editor: Preserve signal line shape when moving and resizing blocks.

❇️MATLAB:
- Local Functions: Define functions anywhere in scripts and live scripts.
- Python Interface: Convert between MATLAB tables and Python Pandas DataFrames.
- Python Interface: Interactively run Python code with Run Python Live Editor task.
- REST Function Service: Call MATLAB functions from any local or remote client program using REST.
- Secrets in MATLAB Vault: Remove sensitive information from code.
- ode Object: Solve ODEs and perform sensitivity analysis using SUNDIALS solvers.

❇️Simulink:
- Simulink Solver: Use local solvers for components with faster dynamics.
- Simulation Object: Control the execution and tune parameter values of scripted simulations.
- MATLAB Apps: Create a custom app that interfaces with a Simulink model using MATLAB App Designer.

❇️Support Packages
- 6G Exploration Library for 5G Toolbox
- Audio Toolbox Interface for SpeechBrain Library
- Computer Vision Toolbox Model for Pose Mask R-CNN 6-DOF Object Pose Estimation
- Databricks ODBC Driver
- Embedded Coder Support Package for Infineon AURIX TC3x Processors
- Lidar Toolbox Model for RandLA-Net Semantic Segmentation
- Lidar Toolbox Support Package for Hokuyo Lidar Sensors
- MariaDB ODBC Driver
- PostgreSQL ODBC Driver

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#matlab_2024

⚜️Neural network course session one::
1️⃣Introduction to Neural Networks

🔵This video provides an introduction to the fascinating world of neural networks. We explore the biological inspiration behind artificial neural networks, drawing parallels between the human brain and these computational models. Key topics covered include:

✅History of neural networks and major milestones
✅Comparison of biological and artificial neuron speeds
✅Loss of neurons with age and neuroplasticity
✅How the brain processes information and learns
✅Applications of neural networks across diverse fields
✅Further reading resources on neural network fundamentals
To see the next meeting earlier, visit the YouTube
🔻YouTube: second session
https://youtu.be/JtBebQ2CJKs

Download file and codes (in comment)::
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#NeuralNetworks #ArtificialIntelligence #MachineLearning #Neurons #BrainInspired #Neuroplasticity #DeepLearning #AI #AINeuralNetworks #ComputationalNeuroscience #NeuralNetworkApplications

🔺Fuzzy System Optimization Step-by-Step: Enhancing Interpolation with Genetic Algorithms🔻:

✳️In this detailed tutorial, we dive into the complex world of fuzzy system optimization using a genetic algorithm. Watch as we methodically enhance a fuzzy model to predict outputs more accurately through successive generations of optimization. Starting with the basics, the video explains the generation of membership functions for inputs and outputs and how they evolve through various iterations to minimize error.

🔻YouTube: https://youtu.be/KXM-diXXEyE
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#FuzzyLogic #GeneticAlgorithm #SystemOptimization #MachineLearning #ArtificialIntelligence #DataScience #EngineeringTutorials #MATLAB #OptimizationTechniques #AlgorithmDevelopment #MATLAB_2024

کورس LLM دانشگاه شریف

این ترم دانشکده کامپیوتر شریف کورسی رو در مقطع تحصیلات تکمیلی با موضوع LLM‌ها (مدل‌های‌زبانی بزرگ) و مسائل مربوط به اونها با تدریس مشترک دکتر سلیمانی، دکتر عسگری و دکتر رهبان ارائه کرده. خوبی این کورس اینه که به صورت جامع و کاملی انواع مباحث موردنیاز رو بحث کرده (از معرفی معماری ترنسفورمری گرفته تا فرآیند‌های جمع آوری داده و روش‌های PEFT و ...) از همه اینها مهمتر، فیلم‌ها و تمرین‌های این کورس هم به صورت پابلیک در لینک درس قرار می‌گیرن. از دست ندید.

لینک کورس:
sharif-llm.ir

لینک ویدیوها:
https://ocw.sharif.edu/course/id/524


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#course
#coach

🔰Linear Control Training Workshop - Session 1

🟢This video covers the first session of a comprehensive linear control training workshop. Linear control theory is fundamental to understanding and designing control systems in various engineering applications.

In this session, you'll learn the basics of linear control, including:
🔹 Introduction to control systems and their components
🔸 Modeling linear systems using transfer functions and state-space representations
🔹Analyzing system stability and performance using tools like root locus and frequency response methods
🔸Basic control design techniques like PID control
Whether you're a student, engineer, or professional in the field of control systems, this video will provide a solid foundation for understanding linear control concepts and techniques.
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#LinearControl #ControlSystems #ControlTheory #SystemModeling #SystemStability #ControlDesign #EngineeringEducation