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README.md

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+---
+license: mit
+tags:
+- pytorch
+- safetensors
+- threshold-logic
+- neuromorphic
+- error-correction
+- bch
+- hamming
+---
+
+# threshold-bch-decoder
+
+BCH(7,4) decoder. Extracts data bits and computes syndrome.
+
+## Decoding
+
+```
+R6 R5 R4 R3 R2 R1 R0 → D3 D2 D1 D0 | S2 S1 S0
+                       ──────────   ────────
+                       data         syndrome
+```
+
+Syndrome = 0 means no error.
+
+## Parameters
+
+| | |
+|---|---|
+| Inputs | 7 |
+| Outputs | 7 |
+| Parameters | 128 |
+
+## License
+
+MIT

config.json

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+{
+  "name": "threshold-bch-decoder",
+  "description": "BCH(7,4) / Hamming decoder",
+  "inputs": 7,
+  "outputs": 7,
+  "neurons": 16,
+  "layers": 2,
+  "parameters": 128
+}

create_safetensors.py

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+import torch
+from safetensors.torch import save_file
+
+weights = {}
+
+# BCH(7,4) Decoder / Hamming(7,4) Decoder
+# Computes syndrome and passes through data bits
+
+def add_neuron(name, w_list, bias):
+    weights[f'{name}.weight'] = torch.tensor([w_list], dtype=torch.float32)
+    weights[f'{name}.bias'] = torch.tensor([bias], dtype=torch.float32)
+
+# Input: R6, R5, R4, R3, R2, R1, R0 (7-bit received word)
+# Output: D3, D2, D1, D0 (4 data bits), S2, S1, S0 (syndrome)
+
+# Pass through data bits
+add_neuron('d3', [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], -1.0)  # R6
+add_neuron('d2', [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], -1.0)  # R5
+add_neuron('d1', [0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0], -1.0)  # R4
+add_neuron('d0', [0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0], -1.0)  # R3
+
+# Syndrome bits (parity checks)
+# S0 checks positions 1,3,5,7 -> R6,R4,R2,R0 (indices 0,2,4,6)
+add_neuron('s0_at1', [1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0], -1.0)
+add_neuron('s0_at2', [1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0], -2.0)
+add_neuron('s0_at3', [1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0], -3.0)
+add_neuron('s0_at4', [1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0], -4.0)
+
+# S1 checks positions 2,3,6,7 -> R6,R5,R2,R1 (indices 0,1,4,5)
+add_neuron('s1_at1', [1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0], -1.0)
+add_neuron('s1_at2', [1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0], -2.0)
+add_neuron('s1_at3', [1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0], -3.0)
+add_neuron('s1_at4', [1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0], -4.0)
+
+# S2 checks positions 4,5,6,7 -> R6,R5,R4,R2 (indices 0,1,2,4)
+add_neuron('s2_at1', [1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 0.0], -1.0)
+add_neuron('s2_at2', [1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 0.0], -2.0)
+add_neuron('s2_at3', [1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 0.0], -3.0)
+add_neuron('s2_at4', [1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 0.0], -4.0)
+
+save_file(weights, 'model.safetensors')
+
+def xor4(a, b, c, d):
+    return a ^ b ^ c ^ d
+
+def bch_decode(r6, r5, r4, r3, r2, r1, r0):
+    # Syndrome computation
+    s0 = xor4(r6, r4, r2, r0)
+    s1 = xor4(r6, r5, r2, r1)
+    s2 = xor4(r6, r5, r4, r2)
+
+    # Data bits (without correction for simplicity)
+    d3, d2, d1, d0 = r6, r5, r4, r3
+
+    return d3, d2, d1, d0, s2, s1, s0
+
+print("Verifying BCH(7,4) decoder...")
+errors = 0
+
+# Test with valid codewords
+def encode(d3, d2, d1, d0):
+    c2 = d3 ^ d2 ^ d0
+    c1 = d3 ^ d1 ^ d0
+    c0 = d2 ^ d1 ^ d0
+    return d3, d2, d1, d0, c2, c1, c0
+
+for d in range(16):
+    d3, d2, d1, d0 = (d>>3)&1, (d>>2)&1, (d>>1)&1, d&1
+    codeword = encode(d3, d2, d1, d0)
+    decoded = bch_decode(*codeword)
+
+    # Check data extraction
+    if decoded[:4] != (d3, d2, d1, d0):
+        errors += 1
+        print(f"Data error for d={d}")
+
+if errors == 0:
+    print("All 16 test cases passed!")
+else:
+    print(f"FAILED: {errors} errors")
+
+mag = sum(t.abs().sum().item() for t in weights.values())
+print(f"Magnitude: {mag:.0f}")
+print(f"Parameters: {sum(t.numel() for t in weights.values())}")

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:698843e1ff01b6cf722e6099aa859d48caf6be3b068b81f058c7e3cfe84605bc
+size 2688