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THE CONSCIOUSNESS ATLAS
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ConsciousnessLearn · Explore · Joseph Anady

Shannon entropy H(X) = -Σ p(x) log p(x) · @brief Shannon entropy H(X)

This relation defines @brief Shannon entropy H(X) in the source section “Shannon entropy H(X) = -Σ p(x) log p(x) · @brief Shannon entropy H(X)”. It specifies the displayed relationship between the named quantities or parameters. Its interpretation depends on the…

Implementation mathematicsSource recovered; runtime not executed
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Understand information

Learn to distinguish probabilities, logarithm conventions, and information quantities.

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gh-eq-cd95bbcc554a3151source-comment-equation
@briefShannonentropyH(X)=−Σp(x)logp(x)@brief Shannon entropy H(X) = -Σ p(x) log p(x)

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This relation defines @brief Shannon entropy H(X) in the source section “Shannon entropy H(X) = -Σ p(x) log p(x) · @brief Shannon entropy H(X)”. It specifies the displayed relationship between the named quantities or parameters. Its interpretation depends on the source’s stated variables and conditions; this record does not assign an unprovided physical or cognitive meaning to them.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

  1. Read @brief Shannon entropy H(X) as the quantity being defined or updated by this relation.

  2. Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.

  3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

  • This source expression was recovered from the pinned code revision. Its presence does not establish that the associated program was built, run, or scientifically validated.

Original context

Read the surrounding source passage
}

// ═══════════════════════════════════════════════════════════════════════════════
// II. INFORMATION THEORY
// ═══════════════════════════════════════════════════════════════════════════════

/**
 * @brief Shannon entropy H(X) = -Σ p(x) log p(x)
 */
inline double shannon_entropy(const double* probs, size_t n) {
    double h = 0.0;
    for (size_t i = 0; i < n; ++i) {
        if (probs[i] > 1e-10) {
            h -= probs[i] * std::log2(probs[i]);
        }
    }
    return h;
}
Exact original notation
@brief Shannon entropy H(X) = -Σ p(x) log p(x)

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