ComputingNotes

Multi Agent Reinforcement Learning

by ComputingNotes
What is an Agent? The three core characteristics of an autonomous system. 1 Autonomous Entity It operates independently as a self-directed entity, without requiring constant human intervention or manual control. 2 Observes Environment It continuously monitors its surroundings, gathering real-time state data and information about the world around it. 3 Chooses How to Act Based ... Read More

Data Structure and Algorithms – Trees

by ComputingNotes
Data Structures: Tree Basics A tree is a non-linear hierarchical data structure consisting of nodes connected by edges. Hover over nodes to see their terminology. Root Internal Leaf Leaf Leaf Hover over a node to see terminology… N-ary Trees A tree where a node can have at most N children. This example shows a 4-ary ... Read More

Barrage Relay Network – Barrage Relay, Cooperation and BAC

by ComputingNotes
System Initializing… A B C TDMA Frame 1 A TDMA Frame 2 Barrage Relay How data floods a Barrage Relay Network slot-by-slot TDMA Frame 1 • Slot A The Initial Broadcast The central Source node (black) transmits the first packet. This is visualized as the first expanding blue wave. All nodes that successfully receive this ... Read More

Phase Dithering and Modern Error Correction

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How Networks Survive Chaos Understanding Phase Dithering and Modern Error Correction Transmitter 1 (Static) Transmitter 2 (Dithering) Receiver (Composite Sum) Phase Dithering When multiple antennas transmit the exact same signal simultaneously, there is a risk that the waves will collide out-of-phase and permanently cancel each other out (destructive interference). Phase Dithering is a deliberate, pseudo-random ... Read More

Frequency, Amplitude and Phase: RF Characteristics

by ComputingNotes
The 3 Core RF Characteristics Understanding how wireless signals travel and interact Frequency Tuning Measured in Hertz (Hz), frequency represents the number of complete wave cycles that occur in exactly one second. Analogy: Just like childhood walkie-talkies, the transmitter and receiver must be tuned to the exact same frequency (channel) to communicate. Amplitude Power Amplitude ... Read More

Hashing, Hash Tables and Scatter Tables

by ComputingNotes
1. Hashing The process of transforming input data (a Key) of any size into a fixed-size value (a Hash). This value is usually a single number. 2. Hash Table A data structure that stores Key-Value pairs. It uses Hashing to calculate an index into an array, allowing you to find any entry instantly (O(1)). 3. ... Read More

Fundamental Data Structures – DSA

by ComputingNotes
1. Dynamic Arrays A dynamic array grows automatically when it runs out of space. Watch what happens when the capacity (initially 4) is reached! Push Element Reset Current Capacity: 4 | Elements: 0 Real-World Examples: Shopping Carts: E-commerce sites use dynamic arrays to store items in your cart because they don’t know how many items ... Read More

Data Encoding – Quantum Machine Learning

by ComputingNotes
For classical data to be used by quantum circuit, it needs to be encoded which is called data encoding. In qiskit, we can use tools like z_feature_map or zz_feature_map etc. which includes rotation layers and entangling layers. Normalization is required in quantum machine learning similar to in classical machine learning. Normalization Before classical data can ... Read More

Matrix Transformations – Linear Algebra

by ComputingNotes
1. Functions and Transformations In standard algebra, a function takes a single number as an input and outputs a new number: f(x) = y. In Linear Algebra, we scale this concept up. A Transformation (often denoted as T) is a mathematical rule that takes an entire Vector as an input and assigns it to a ... Read More

Algebraic Properties of Matrices

by ComputingNotes
1. Properties of Matrix Arithmetic Matrix arithmetic shares many rules with standard algebra, but there are crucial differences. Here are the core laws: Commutative Law for Addition: A + B = B + A Associative Law: A + (B + C) = (A + B) + C A(BC) = (AB)C Distributive Law: A(B + C) ... Read More
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