🔍 Gate Level Perceptron

• This project explores pattern recognition at logic-gate level.

• It began as an attempt to build perceptron-like system for recognizing patterns, but early versions evolved into a strictly logical pattern relation anlyzer using strict boolean logic.

• Subsequent versions transitioned from rigid equivalence checks to popcount-based scoring and threshold decisions, moving the architecture toward a true perceptron and, eventually self learning behaviour.

θ = 7 & M = 8, M > θ: hence Pattern is recognized ✅

θ = 9 & M = 8, M ≤ θ: hence Pattern is not recognized ❌

🧱 Versions Built

• Version 0: A pattern relation analyzer that classifies how an input pattern relates to a stored pattern, enforces rule based recognition rather than learning.

  • Detector_v0.0 -> Recognizes the pattern and sub-patterns if they are inside the boundary set up by weights-grid.
  • Detector v0.1 -> Recognizes the pattern and super-patterns if they are outside the boundary set up by weights-grid.
  • Detector v0.2 -> Classifies the input as a sub-pattern, super-pattern, anti-pattern or equivalence precisely through a 2-POV logical analysis.

• Version 1: Pop-count based judgement against a variable Threshold instead of perfect equivalence check, takes us one step closer to self-learning machines.

  • Detector_v1.0 -> Recognizes the pattern if total number of matched pixels are greater than the set threshold.

💻 Verilog Implementation

• Detector_v0.0

Equivalence & Sub-Pattern Recognition 🔹

• Detector_v0.1

Equivalence & Super-Pattern Recognition 🟦

• Detector_v0.2

Equivalence & Super & Sub & Anti-Pattern Recognition 🔹🟦

🔜 Future Versions

• Feedback-driven adaptation on top of the existing popcount-based judgement mechanism.
• Automatic threshold adjustment based on feedback which would allow the detector to gradually converge towards an apropriate threshold.
• It would form basis of simple self-learning adaptive system.

🛠️Current Development:

• Population Counter Developed and operation verified ✓
• Comparator Developed for comparing the Pop-count(M) with the threshold(θ) to make decisions ✓
• Pop-Count based pattern detector developed and tested ✓
• Detector Version 0 series implemented in Verilog ✓

📜License

• Source code and HDL files are licensed under the MIT License.
• Documentation, diagrams, images, and PDFs are licensed under Creative Commons Attribution 4.0 (CC BY 4.0).