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ConsciousnessLearn · Explore · Joseph Anady

Compression family: monotone magnitude subtraction

This rule subtracts 0.05 times the absolute input. Applied in isolation, it never increases x and can decrease it without bound under a persistently nonzero input. It supplies a numerical penalty; an actual compression claim also needs an encoding, output size,…

Implementation mathematicsSource recovered; runtime not executed
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gh-eq-b8126d2512fe18fedocumented-equation
f12(x)=x−0.05⋅∣dxnorm∣f₁₂(x) = x - 0.05 · |dx_norm|

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This rule subtracts 0.05 times the absolute input. Applied in isolation, it never increases x and can decrease it without bound under a persistently nonzero input. It supplies a numerical penalty; an actual compression claim also needs an encoding, output size, decoding procedure, and fidelity criterion.

Terms & definitions

TermMeaning in this source
x

Current scalar state

dx_norm

Input whose absolute magnitude sets the decrement

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## 3.13 Family 12: Compression / Rate Control

```
f₁₂(x) = x - 0.05 · |dx_norm|
```

**Equation Type**: Compression: minimize description length

**Explanation**: Actively reduces complexity by damping large changes. Used for finding minimal representations.

## 3.14 Family 13: Memory Trace (Zecher)

```
f₁₃(x) = x + 0.02 · (dx_norm + utility)
```

**Equation Type**: Trace accumulation: x'_i = Σ f_i : dΩ

**Explanation**: Slowly accumulates both change and utility signals, creating persistent memory traces. Named "Zecher" (Hebrew for "memory").

## 3.15 Family 14: Decisive Action / Policy

```
f₁₄(x) = x + 0.15 · softsign(utility) - 0.05 · ed_error
Exact original notation
f₁₂(x) = x - 0.05 · |dx_norm|

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