threshold-sr-latch

SR (Set-Reset) latch next-state logic as threshold circuit. Computes next state given current inputs and previous state.

Circuit

S      ──┐
R      ──┼──► SR Latch ──┬──► Q
Q_prev ──┘               └──► Qn

Truth Table

S	R	Q_prev	Q	Qn	Mode
0	0	0	0	1	Hold
0	0	1	1	0	Hold
0	1	X	0	1	Reset
1	0	X	1	0	Set
1	1	X	0	0	Invalid

Classic NOR Implementation

     S ──┬──►[NOR]──► Qn
         │      ▲
         │      │
         │      └─────┐
         │            │
     R ──┴──►[NOR]──► Q
              ▲       │
              │       │
              └───────┘

Cross-coupled NOR gates create feedback loop.

Combinational Representation

This circuit models the next-state function:

• Input: S, R, and Q_prev (previous Q)
• Output: Q_next, Qn_next

True latch behavior requires feeding Q output back to Q_prev over time.

Architecture

Component	Neurons
Input inversions	6
Hold logic	2
Output gates	3

Total: 11 neurons, 39 parameters, 4 layers

Usage

from safetensors.torch import load_file

w = load_file('model.safetensors')

# Simulate latch over time:
q = 0
for s, r in [(1,0), (0,0), (0,1), (0,0)]:
    q_next = compute_q(s, r, q, w)
    q = q_next

Files

threshold-sr-latch/
├── model.safetensors
├── create_safetensors.py
├── config.json
└── README.md

License

MIT