Stochastic equations can solve problems faster for various scientific problems as well as AI training. Instead of eliminating noise, drift and randomness in the circuits, which are prerequisites in ...

Stochastic computing is one of logic’s little gems. Its advantage is essentially that it makes multiplication as easy as addition. That’s significant. Imagine adding 0.4397625 and 0.8723489. It’s a ...

A new technical paper titled “All-in-Memory Stochastic Computing using ReRAM” was published by researchers at TU Dresden, Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), ...

According to computational complexity theory, mathematical problems have different levels of difficulty in the context of their solvability. While a classical computer can solve some problems (P) in ...

Those who design deep neural networks for artificial intelligence often find inspiration in the human brain. One of the brain’s more important characteristics is that it is a “noisy” system: not every ...

Covering developments in neuromorphic computing has been something of a piecemeal experience, as happens with all novel architectures. There are few companies with scalable devices and the research is ...

This is a preview. Log in through your library . Abstract Random walks are a fundamental model in applied mathematics and are a common example of a Markov chain. The limiting stationary distribution ...

This is a preview. Log in through your library . Abstract In this paper, we present a unified approach to study a class of cooperative games arising from inventory centralization. The optimization ...