Low-discrepancy Sobol sequences speed bit-stream convergence in stochastic computing, cutting latency, energy use, and hardware footprint.
An incoherent optical source and delay interferometer generate wideband random noise for ADC dithering, improving SFDR with lower power.
Alpha particles from a thin-film radioactive isotope strike a photodiode to create true random pulses for compact IoT security hardware.
Dynamic ECC path selection routes critical data through dual correction engines while keeping general writes faster and flash memory wear lower.
Multiple output samples guide iterative ADC compensation code selection, improving calibration precision and random number quality.
Multiple ring oscillators use counter-based correlation checks to detect interference before synchronization degrades true random number generation.
Deterministic shuffling and sub-sampling cut stochastic computing latency, area, and correlation errors while preserving parallel unary computation.
Magnetic particle diffusion and thermal noise decorrelate random input signals in a compact, low-energy electrical signal architecture.
Encoded data fragments let distributed storage recover from partial node availability, maintaining continuity while lowering running costs.
Dual avalanche photodiodes use dark-electron avalanches and feedback bias control to deliver unbiased random bits without external particle sources.
Multiple scrambled sequences are compared to store the one with fewer logical highs, cutting multi-level cell bit errors and improving read accuracy.
Pseudorandom code shifting changes which DAC cells are activated, cutting harmonic distortion and noise from cell mismatch.
Multiple entropy source circuits and XOR combining raise true random number output while limiting phase deviation in high-speed systems.
Parallel OTPM cells use controlled avalanche breakdown and current limiting to generate unbiased random bits without complex post-processing.
Hot carrier injection and biasing tune cell circuits between stable PUF behavior and RNG randomness to strengthen device authentication.
Models transmission errors with a Markov-modulated Bernoulli process to choose generator polynomials with more accurate residual error estimates.
Using PWM pulse signals instead of stochastic bit streams cuts SNG hardware cost and power while preserving fault-tolerant computation.
Thermal diffusion of magnetic particles decorrelates stochastic signals in a submicron architecture, cutting filter size and energy use.
LSB-level random sequence injection estimates noise transfer impulse response, enabling adaptive loop-delay correction in sigma-delta ADCs.
Multiple entropy loops sample inverter outputs in parallel and combine them with XOR logic to raise true random generation speed.
Cross-coupled inverters and capacitors store threshold-voltage differences, then settle randomly to reduce deterministic bias in RNG output.
A stochastic digital generator replaces analog pink-noise filters to deliver tunable 1/f output with precise amplitude control and no low-frequency cutoff.
Random digital sequences drive ADC sampling capacitors for self-calibration, correcting capacitance variation without external signals.
Calibration separates quantum tunneling fluctuations from external noise so random bit extraction delivers more reliable entropy for cryptographic use.
Varying the number of passed clock pulses makes the clock harder to predict while preserving a controllable processing speed.
Adjustable delay elements balance metastable ring timing despite manufacturing dispersion, helping generate truly random numbers reliably.
Battery voltage variability supplies entropy for secure PRNG seeding, improving cryptographic randomness without extra hardware.