Stanislaw Andrzej Wozniak

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Neuromorphic systems provide brain-inspired methods of computing. In a neuromorphic architecture, inputs are processed by a network of neurons receiving operands through synaptic interconnections, tuned in the process of learning. Neurons act simultaneousl ...

This review provides a high-level synthesis of significant recent advances in artificial neural network research, as well as multi-disciplinary concepts connected to the far-reaching goal of obtaining intelligent systems. We assume that a global outlook of ...

Neuromorphic systems using memristive devices provide a brain-inspired alternative to the classical von Neumann processor architecture. In this work, a spiking neural network (SNN) implemented using phase-change synapses is studied. The network is equipped ...

Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that theoretical resul ...

Stanislaw Andrzej Wozniak

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Unsupervised Learning of Phase-Change-Based Neuromorphic Systems

Review of Advances in Neural Networks: Neural Design Technology Stack

Unsupervised Learning Using Phase-Change Synapses and Complementary Patterns

High-performance deep spiking neural networks with 0.3 spikes per neuron

Review of Advances in Neural Networks: Neural Design Technology Stack