All digital circuits use sequences of logic gates that implement Boolean functions to store and transmit binary information. Threshold logic gates receive multiple input signals and produce a single output if the number of signals is below a hardwired threshold value, and can therefore process any Boolean function that might otherwise require multiple...

Background Neuromorphic computing, or the concept of designing systems that mimic the adaptability and learning exhibited by biological neural processes, is the future of computing design. This type of computing is ideal for use in the Internet of Things (IoT) movement, which refers to the embedding of internet computing devices into everyday objects....

Background Neuro-inspired machine deep learning have demonstrated that they can perform complex tasks such as image and speech classification, object recognition, and real-time decision-making. The state-of-the-art deep learning algorithms employ neural networks which have millions of parameters. Deploying such deep neural networks onto mobile platforms...

Traditional Boolean computing methods are reaching their physical limits. Neuromorphic computing—a system engineered to mimic neuro-biological architectures present in the nervous system—has gained great attention as an alternative. Large scale neural networks consist of a massive number of synapses that connect between groups of neurons....