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Numerical Computing Potential<\/h4>\n<p>MATLAB is an environment for programming in numerical computing and analysis, providing a powerful toolset for solving complex problems in various industries. Its extensive libraries and built-in functions enable users to manipulate matrices, visualize data, and build mathematical models. With MATLAB, researchers and engineers can efficiently simulate and visualize complex systems, deploy solutions, and prototype new ideas. The software&#8217;s robust machine learning capabilities and signal processing tools make it an indispensable asset for data-driven decision-making. MATLAB&#8217;s user-friendly interface and vast community support ensure that users can quickly adapt to new technologies and tackle even the most challenging projects. By harnessing the power of MATLAB, individuals and organizations can unlock new levels of innovation and productivity.<\/p>\n<h4>Industry Applications and Use Cases<\/h4>\n<h4>1. Machine Learning and AI<\/h4>\n<ul>    \u2022 Develop predictive models for image recognition, natural language processing, and recommender systems    \u2022 Implement machine learning algorithms, including deep learning, for complex problem-solving    \u2022 Utilize MATLAB&#8217;s built-in tools for data preprocessing, feature extraction, and model validation<\/ul>\n<h4>2. Signal Processing and Acoustics<\/h4>\n<table>\n<tr>\n<th>Toolbox<\/th>\n<th>Description<\/th>\n<\/tr>\n<tr>\n<td>Signal Processing Toolbox<\/td>\n<td>Contains functions for signal filtering, modulation, and demodulation, as well as audio processing and analysis<\/td>\n<\/tr>\n<tr>\n<td>Acoustics Toolbox<\/td>\n<td>Provides functions for acoustic analysis, signal processing, and audio modeling<\/td>\n<\/tr>\n<\/table>\n<h4>3. Control Systems and Robotics<\/h4>\n<ul>    \u2022 Design and simulate control systems for autonomous vehicles, robots, and other complex systems    \u2022 Use MATLAB&#8217;s control systems toolbox to model and analyze nonlinear systems    \u2022 Develop and test control strategies for stability, optimality, and performance<\/ul>\n<h4>4. Data Visualization and Reporting<\/h4>\n<h4>1. Plotting and Charting<\/h4>\n<ul>    \u2022 Create custom plots and charts for data visualization and presentation    \u2022 Utilize MATLAB&#8217;s built-in plotting tools for 2D and 3D visualizations    \u2022 Implement interactive visualizations for real-time data exploration<\/ul>\n<h4>2. Data Analysis and Reporting<\/h4>\n<ul>    \u2022 Perform statistical analysis and data mining using MATLAB&#8217;s built-in tools    \u2022 Develop and deploy reports for data-driven decision-making    \u2022 Create interactive dashboards for data exploration and visualization<\/ul>\n<h4>5. Collaboration and Sharing<\/h4>\n<ul>    \u2022 Share code and collaborate with others using MATLAB&#8217;s built-in version control and sharing tools    \u2022 Utilize MATLAB&#8217;s online platforms for code hosting, documentation, and project management    \u2022 Participate in the MATLAB community for knowledge sharing, networking, and professional development<\/ul>\n<h4>Frequently Asked Questions<\/h4>\n<h4>1. What is MATLAB used for?<\/h4>\n<p>MATLAB is used for a wide range of applications, including numerical computing, machine learning, signal processing, control systems, data visualization, and collaboration.<\/p>\n<h4>2. Is MATLAB user-friendly?<\/h4>\n<p>Yes, MATLAB has a user-friendly interface and extensive documentation, making it accessible to users of all skill levels.<\/p>\n<h4>3. Can I use MATLAB for real-time applications?<\/h4>\n<p>Yes, MATLAB provides tools and functions for real-time applications, including embedded systems, control systems, and signal processing.<\/p>\n<h4>4. Is MATLAB free?<\/h4>\n<p>No, MATLAB is a commercial product, but it offers a free trial version and a student license program for educational institutions.<\/p>\n<h4>5. Can I run MATLAB on my personal computer?<\/h4>\n<p>Yes, MATLAB can be installed on personal computers, but it requires a valid license and a compatible operating system.<\/p>\n<ul>\n<li>Patch installer enabling seamless permanent activation<\/li>\n<li>MATLAB Crack exe Multi-Core Pro Unlocked Ultimate FREE<\/li>\n<li>Multi-license key handler with randomizer<\/li>\n<li>MATLAB Crack + Keygen [Win-x64] [Full Version] FREE<\/li>\n<li>License key updater allowing easy license transfers<\/li>\n<li>MATLAB Crack Only Native x64 [Activated] Genuine FREE<\/li>\n<li>Fully automated patch \u2013 no user input needed<\/li>\n<li>MATLAB R2024a Crack 2027 [2027 Ready] Enterprise 2026<\/li>\n<li>Activation key tool supporting multiple license types<\/li>\n<li>MATLAB Crack + License Native x64 Pre-Activated 2026 FREE<\/li>\n<\/ul>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube.com\/embed\/7f50sQYjNRA\" width=\"560\" height=\"315\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p><a href='https:\/\/iglta.co.za\/category\/skippers\/'>https:\/\/iglta.co.za\/category\/skippers\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ud83d\udcd8 Build Hash: 54504e24647c35adaaf9a1dc56fc51ef \u2022 \ud83d\uddd3 2026-10-20 Verify Processor: Dual-core for keygens RAM: 4 GB for keygen Disk space: Enough for tools Unlocking Numerical Computing Potential MATLAB is an environment for programming in numerical computing and analysis, providing a powerful toolset for solving complex problems in various industries. Its extensive libraries and built-in functions enable [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[29],"tags":[],"class_list":["post-882","post","type-post","status-publish","format-standard","hentry","category-emulators"],"_links":{"self":[{"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/posts\/882","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/comments?post=882"}],"version-history":[{"count":1,"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/posts\/882\/revisions"}],"predecessor-version":[{"id":883,"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/posts\/882\/revisions\/883"}],"wp:attachment":[{"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/media?parent=882"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/categories?post=882"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hoomat.ca\/index.php\/wp-json\/wp\/v2\/tags?post=882"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}