Coupled Networks With Feedback-Controlled Resistance Learning

The patent merges memory and processing functions into a unified neuromorphic architecture where synaptic weights are physically embodied in conductive materials. This eliminates the von Neumann bottleneck by allowing simultaneous storage and computation, where the same physical structure performs both memory retention and computational operations through analog voltage dynamics.

The patent replaces digital mechanical switching and sequential processing with continuous analog electrical dynamics. Conductive materials with varying conductivity states substitute for discrete memory cells and logic gates, enabling parallel computation through physical field interactions rather than sequential electronic switching.

The patent segments the centralized processing function into distributed synaptic units across the neuromorphic network. Each synapse independently stores and processes information through its conductive state, eliminating single points of failure. The system architecture divides functionality across many identical, independent elements rather than relying on centralized control logic.

The patent employs homogeneous synaptic units with identical structural properties throughout the network. Each synapse uses the same conductive material and operational principles, allowing any damaged unit to be replaced or bypassed without affecting overall system functionality. The uniformity of synaptic elements enables redundant computation and graceful degradation under damage conditions.

The patent replaces complex, power-intensive digital potentiometers with simple, passive conductive materials that require no active control circuitry. These conductive elements achieve sufficient precision through their inherent physical properties and can be replaced or reconfigured through simple physical processes rather than complex electronic control, dramatically reducing device complexity and power consumption.

The patent substitutes electronic digital control mechanisms with physical material properties. Instead of using digitally controlled potentiometers requiring power and complex circuitry, the system uses conductive materials whose resistance is determined by their physical state, achievable through simple fabrication processes or physical manipulation rather than electronic control.