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--- |
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license: mit |
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tags: |
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- pytorch |
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- safetensors |
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- threshold-logic |
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- neuromorphic |
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- sequential |
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- latch |
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--- |
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# threshold-d-latch |
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D latch (level-sensitive) next-state logic as threshold circuit. |
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## Circuit |
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``` |
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E ───────┐ |
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D ───────┼──► D-Latch ──┬──► Q |
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Q_prev ──┘ └──► Qn |
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``` |
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## Modes |
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- **E=1 (Transparent):** Q follows D |
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- **E=0 (Hold):** Q holds previous value |
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## Truth Table |
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| E | D | Q_prev | Q | Qn | Mode | |
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|---|---|--------|---|----|----| |
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| 0 | X | 0 | 0 | 1 | Hold | |
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| 0 | X | 1 | 1 | 0 | Hold | |
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| 1 | 0 | X | 0 | 1 | Transparent | |
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| 1 | 1 | X | 1 | 0 | Transparent | |
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## Logic |
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``` |
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Q = (E AND D) OR (NOT_E AND Q_prev) |
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Qn = (E AND NOT_D) OR (NOT_E AND NOT_Q_prev) |
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``` |
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## Architecture |
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| Layer | Neurons | |
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|-------|---------| |
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| 1 | e_and_d, e_and_notd, note_and_qprev, note_and_notqprev | |
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| 2 | Q, Qn | |
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**Total: 6 neurons, 26 parameters, 2 layers** |
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## D-Latch vs D-Flip-Flop |
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- **D-Latch:** Level-sensitive. Q changes while E is high. |
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- **D-Flip-Flop:** Edge-triggered. Q changes only on clock edge. |
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D-latches are simpler but can cause timing issues (race conditions) if not carefully designed. Flip-flops are safer for synchronous designs. |
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## Parameters |
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|---|---| |
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| Inputs | 3 | |
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| Outputs | 2 | |
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| Neurons | 6 | |
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| Layers | 2 | |
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| Parameters | 26 | |
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| Magnitude | 18 | |
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## Usage |
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```python |
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from safetensors.torch import load_file |
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w = load_file('model.safetensors') |
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# Simulate latch behavior |
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q = 0 |
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for e, d in [(1, 1), (1, 0), (0, 1), (0, 0)]: |
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q_next = compute(e, d, q, w) |
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q = q_next |
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``` |
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## License |
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MIT |
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