An arithmetic apparatus adjusts input period duration based on positive weight ratios to generate multiply-accumulate signals.
A list structure control circuit manages data insertion and removal using position selection signals to update memory states efficiently.
A correlithm object processing system aligns linear string objects to identify similar data samples through direct bitwise operations.
An infinity computer processes infinite and finite numbers using a new arithmetic logic unit.
Dual-path floating-point adder splits inputs based on exponent differences, supporting intermediate precisions without increasing circuit area.
A computing apparatus generates neural network loss and predicts hardware resources to determine a target architecture.
Approximation circuitry reduces power consumption by processing only significant bits of operands.
Fixed-point arithmetic replaces floating-point operations in neural network training, reducing energy consumption while maintaining convergence stability.
A signal processing device generates analysis object data and performs product-sum operations on template data to detect synchronous timing.
A simplified sigmoid circuit uses variational transformations to approximate neural network functions efficiently.