Neural Network Components (jlnn.nn)¶
This section contains implementations of logic gates as NNX modules and tools for working with the computational graph.
- Base Logical Elements
- Parameter Constraints
- Functional Logic Kernels
and_drastic()and_godel()and_kleene_dienes()and_lukasiewicz()and_physical_kleene_dienes()and_physical_lukasiewicz()and_physical_reichenbach()and_product()and_reichenbach()bulk_and_drastic()bulk_and_godel()bulk_and_product()bulk_or_drastic()bulk_or_godel()bulk_or_product()implication()implication_godel()implication_goguen()implication_kleene_dienes()implication_lukasiewicz()implication_physical_kleene_dienes()implication_physical_lukasiewicz()implication_physical_reichenbach()implication_reichenbach()logical_not()or_drastic()or_godel()or_kleene_dienes()or_lukasiewicz()or_physical_kleene_dienes()or_physical_lukasiewicz()or_physical_reichenbach()or_product()or_reichenbach()weighted_and()weighted_and_godel()weighted_and_kleene_dienes()weighted_and_product()weighted_and_reichenbach()weighted_implication()weighted_nand()weighted_nand_kleene_dienes()weighted_nand_reichenbach()weighted_nor()weighted_nor_kleene_dienes()weighted_nor_reichenbach()weighted_not()weighted_or()weighted_or_godel()weighted_or_kleene_dienes()weighted_or_product()weighted_or_reichenbach()weighted_xor_godel()weighted_xor_lukasiewicz()weighted_xor_product()xor_godel()xor_product()- Key features
- The core of Łukasiewicz’s logic
- Traditional and parametric operators
- A complex apparatus of implications
- Logical Gates (Stateful)
BulkAndBulkOrPhysicalAndPhysicalImplicationPhysicalNandPhysicalNorPhysicalNotPhysicalOrWeightedAndWeightedImplicationWeightedNandWeightedNorWeightedNotWeightedOrWeightedXor- Stateful Gates vs. Stateless Functions
- 1. Traditional parametric logic gates
- 2. Bulk Gates
- 3. Space-time-curved physics gates (PFL)
- Logical Predicates