SelfDescriptionComplexity : Prop ≡
∀k : ℕ . k ≥ 2 →
let Ek = k-ary encoding system in
let Dk = description complexity of Ek in
let Ck = encoding capacity of Ek in
SelfReferentialComplete(S) → Dk ≤ Ck
where
Dk ≥ k·log(k) + O(k²) // 描述复杂度下界
Ck = log(k) per symbol // 编码容量
HigherBaseInfeasibility : Prop ≡
∀k : ℕ . k ≥ 3 →
¬(SelfReferentialComplete(Ek) ∧ NonDegenerate(Ek))
where
NonDegenerate(Ek) ≡ All k symbols are actively used
Proof of BaseClassification:
Case k = 0: No symbols, no information → ⊥
Case k = 1:
Only one symbol → all states identical
H(S) = log(1) = 0 → no entropy increase
Contradicts axiom → ⊥
Case k ≥ 2:
Requires further analysis...
Proof of SelfDescriptionComplexity:
For k-ary system Ek:
Description_Requirements(Ek):
1. Define k distinct symbols: log(k!) ≥ k·log(k) - k
2. Symbol relationships: ≥ (k-1) independent relations
3. Encoding/decoding rules: O(k) complexity
Total: Dk ≥ k·log(k) + O(k)
Encoding_Capacity(Ek):
Each symbol carries log(k) bits
Need n symbols where n·log(k) ≥ Dk
Critical inequality: n ≥ k + O(k/log(k))
Proof of BinarySpecialProperties:
For k = 2:
Symbol_Definition:
0 := ¬1
1 := ¬0
Properties:
- Pure duality relation
- No external reference needed
- Description complexity: O(1)
- Self-contained definition
For k ≥ 3:
Cannot define all symbols through negation alone
Need additional structure (ordering, etc.)
Description complexity: Ω(k·log(k))
Proof of ConstraintComplexity:
For unique decodability, need pattern constraints
k = 2:
Single forbidden pattern (e.g., "11")
Constraint description: O(1)
k ≥ 3:
If forbid single symbol → degenerate to (k-1)-ary
If forbid length-2 patterns → k² possibilities
Must carefully design constraint set
Constraint description: Ω(k²)
Proof for general k ≥ 4:
Information capacity: I(k) = log(k) per symbol
Description requirement: C(k) ≥ k·log(k) + O(k²)
Critical ratio: C(k)/I(k) ≥ k + O(k²/log(k))
As k increases:
- Description complexity grows as O(k²)
- Encoding capacity grows as O(log(k))
- Gap becomes insurmountable
Therefore: ∀k ≥ 3 . ¬SelfReferentialComplete(Ek)
MetaEncodingProblem:
- Need to encode k(t) itself
- What base for meta-information?
- Infinite regress or fixed base
InformationIdentityProblem:
- Symbol "11" means different things in different bases
- Violates information permanence
- Context-dependent interpretation
EfficiencyLoss:
- Extra space for meta-information
- Reduced effective entropy rate
- Violates minimal entropy principle
def verify_base_classification(k):
if k == 0:
return False, "No symbols"
elif k == 1:
return False, "No entropy increase"
else:
return True, "Requires further analysis"
def verify_binary_special_properties():
# 二进制可以通过纯对偶定义
binary_duality = {
'0': 'not 1',
'1': 'not 0'
}
# 验证自包含性
return len(binary_duality) == 2 and all(
'0' in v or '1' in v for v in binary_duality.values()
)