Channel

MATLAB House :: Channel

@MATLAB_HOUSE

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

332subscribers

+0 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID	-1001682176353
Type	Channel
Username	@MATLAB_HOUSE
Created	Between 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded	7 August 2026
Last confirmed live	7 August 2026
Measurements held	2
Confirmed unchanged	1 time, most recently 7 August 2026
On Telegram	t.me/MATLAB_HOUSE

Growth

2 measurements taken within a single day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 331–333 and does not start at zero.

Measurement log — every subscribers count we have recorded
Measured (UTC)	Subscribers	Change
7 Aug 2026, 17:00	332	no change
7 Aug 2026, 05:47	332	first reading

Engagement

20 posts held, back to 16 April 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 27 March 2025. An engagement rate over an empty window would be a number about nothing.

Reaction mix

23 reactions across 12 posts, in 4 distinct kinds. The most used accounts for 52.2% of them.

Every reaction kind recorded on the sample, most used first
Reaction	Count	Share
👍	12	52.2%
❤	7	30.4%
🔥	3	13.0%
👌	1	4.35%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 13 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 23reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 16 April 2024 to 27 March 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

27 Mar 2025, 16:20 UTC≈1,840 views3 reactionsread 7 August 2026

Video

🎬✨ Title: 🚀 How to Run Local AI Models with MATLAB GUI 🖥🤖 📝📌 Description: Dive into 🌟 local AI using OLLAMA 🦙! Learn to download and run powerful open-source models (DeepSeek-R1 1.5B, Qwen 0.5B) locally and integrate them into an interactive MATLAB GUI chatbot 🛠🎨. 🚀🌟 You'll Learn: - ⚙️ Install OLLAMA quickly 💻✨ - 📥 Easily download DeepSeek-R1 and Qwen 📂 - 🎨 Build a user-friendly chatbot in MATLAB 🤖💬 - 🧠 Test AI log…

❤1👌1🔥1

Signed Naser Pakar

5 Dec 2024, 09:06 UTC672 views3 reactionsread 7 August 2026

Forwarded from @N_U_E_E_SPhoto

📌 انجمن علمی هوش مصنوعی دانشگاه نیشابور با همکاری انجمن های علمی مهندسی پزشکی و مهندسی برق برگزار می‌کند: 💢 اولین رویداد سالانه هوش مصنوعی کاربردی نیشابور با افتخار، میزبان شما در یکی از بزرگترین رویداد های علمی تخصصی سال هستیم ✍ با حضور افتخار آفرین پروفسور اکبرزاده، دانشمند برجسته هوش مصنوعی ایران و حضور متخصصین پزشکی و مدیران شرکت های دانش بنیان 🔴 محور های رویداد: 🎙 سخنرانی ویژه با موضوع AI for every one ⚙ ا…

👍2❤1

Signed Naser Pakar

25 Oct 2024, 17:09 UTC986 views1 reactionsread 7 August 2026

Video

✳️Inverted Pendulum Control: RL + MPC Implementation 1️⃣ Reinforcement Learning Features: - Q-Learning for system identification - Self-learning pendulum balancing - No prior model needed 2️⃣ MPC Implementation: - Real-time optimization - Constraint handling - Precise position/angle control 3️⃣ Hardware: - DC motor (50:1 gearbox) - Dual encoders - STM32 controller - Custom PWM driver 4️⃣ Performance: - Upright st…

❤1

Signed Naser Pakar

25 Oct 2024, 17:00 UTC869 viewsread 7 August 2026

Video

✳️کنترل پاندول معکوس با استفاده از یادگیری تقویتی و کنترل پیش‌بین مدل (MPC) | پروژه عملی 1️⃣. یادگیری تقویتی (Reinforcement Learning): - استفاده شده برای شناسایی اولیه سیستم و پایدارسازی - پیاده‌سازی الگوریتم Q-Learning - یادگیری تعادل پاندول بدون نیاز به مدل اولیه سیستم 2️⃣. کنترل پیش‌بین مدل (Model Predictive Control): - طراحی شده پس از شناسایی سیستم - ارائه کنترل بهینه با در نظر گرفتن محدودیت‌ها - دستیابی به کنت…

Signed Naser Pakar

5 Oct 2024, 06:04 UTC866 views1 reactionsread 7 August 2026

Video

✳️ آموزش طراحی سیستم هدایت، ناوبری و کنترل - Matlab / Simulink / FlightGear قسمت سوم 🔰در این ویدیو آموزشی، شما با نحوه کنترل موشک نقطه‌زن با استفاده از کنترل‌کننده‌ی LQG در محیط Simulink آشنا می‌شوید. این آموزش شامل بررسی مدل فضای حالت یک موشک، نحوه عملکرد سیستم ناوبری و هدایت، و طراحی کنترل‌کننده برای هدایت دقیق موشک است. همچنین، فیلتر کالمن برای تخمین متغیرهای حالت و محاسبه دستورات هدایت با در نظر گرفتن موانع و مو…

👍1

Signed Naser Pakar

5 Oct 2024, 06:02 UTC689 views1 reactionsread 7 August 2026

Video

✳️ آموزش طراحی سیستم هدایت، ناوبری و کنترل - Matlab / Simulink / FlightGear قسمت دوم 🔰در این ویدیو، شما با نحوه شبیه‌سازی یک سیستم هدایت، ناوبری و کنترل (GNC) موشک با استفاده از متلب و سیمیولینک آشنا می‌شوید. در این آموزش، از روش‌های کنترل بهینه و فیلتر کالمن برای تخمین و کنترل استفاده شده است. شما می‌توانید مراحل محاسبه پارامترهای ناوبری مانند آزیموت، طول و عرض جغرافیایی و طراحی کنترل‌کننده‌های بهینه با استفاده از …

👍1

Signed Naser Pakar

5 Oct 2024, 05:58 UTC608 views2 reactionsread 7 August 2026

Video

✳️ آموزش طراحی سیستم هدایت، ناوبری و کنترل - Matlab / Simulink / FlightGear قسمت اول 🔰در این ویدیو یاد می‌گیرید چگونه یک سیستم هدایت، ناوبری و کنترل (GNC) کامل برای یک موشک/راکت که از یک موقعیت تصادفی شروع کرده و به هدف مشخصی می‌رسد، طراحی کنید. در این آموزش از روش‌های LQR / LQG و فیلتر کالمن برای کنترل و تخمین استفاده می‌شود. شما یاد می‌گیرید: 1) چگونگی محاسبه آزیموت، عرض و طول جغرافیایی 2) محاسبه دستورات هدایت، ب…

❤1👍1

Signed Naser Pakar

5 Oct 2024, 05:27 UTC≈1,020 views1 reactionsread 7 August 2026

Video

✳️ Guidance, Navigation and Control System Design - Matlab / Simulink / FlightGear Tutorial 🔰 In this video, you will learn how to build a complete guidance, navigation, and control (GNC) system for a rocket/missile that starts from a random position and reaches a specified target using LQR/LQG and Kalman filtering methods for control and estimation. You will learn: 1) How to calculate azimuth, latitude, and longit…

👍1

Signed Naser Pakar

13 Aug 2024, 09:00 UTC≈1,430 views1 reactionsread 7 August 2026

Video

✳️ Deep Network Designer in MATLAB - Quick Guide 🔰 In this tutorial, you’ll learn how to use MATLAB's Deep Network Designer to build and train deep neural networks effortlessly. Whether you're a beginner or advanced user, this step-by-step guide will help you design custom networks, import pre-trained models, adjust layers and hyperparameters, and train/evaluate your models with ease. Produced by Saeed Heibati and …

👍1

Signed Naser Pakar

27 Jul 2024, 07:53 UTC772 views2 reactionsread 7 August 2026

Video

✳️Deep Belief Network Controller: A Modern Alternative to PID in Simulink 🔰Discover how to replace traditional PID controllers with advanced Deep Belief Network (DBN) controllers in Simulink. This tutorial demonstrates the step-by-step process of implementing a DBN controller, showcasing its advantages over PID in complex control systems. Learn how this cutting-edge AI technique can enhance system performance and ad…

👍2

Signed Naser Pakar

19 May 2024, 17:33 UTC≈1,010 viewsread 7 August 2026

Video

⚜️Neural network course session 🔹Telegram: 🆔 @MATLAB_House @MATLABHOUSE

Signed Naser Pakar

19 May 2024, 17:08 UTC870 views0 reactionsread 7 August 2026

Video

🔰Linear Control Training Workshop - Session 5 🔹Telegram: 🆔 @MATLAB_House @MATLABHOUSE

Signed Naser Pakar

Showing the 12 most recent of 20 posts we hold for @MATLAB_HOUSE. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 629,183 of 1,189,255entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Just Education
@JustEducation · 671 post

Republishes

Channels on the register whose posts this channel has forwarded.

انجمن علمی مهندسی برق دانشگاه نیشابور
@N_U_E_E_S · 4321 post

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

Just Education
@JustEducation · 671 post

Names

Channels on the register whose handles appear in this channel's posts.

نخبگان ایران
@bmniran · 20,7671 post انجمن علمی مهندسی برق دانشگاه نیشابور
@N_U_E_E_S · 4321 post

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 7 August 2026 — this entry's latest reading, not the date you are reading this.

“MATLAB House :: Channel” (@MATLAB_HOUSE), 332 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/MATLAB_HOUSE.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.