IEEE transactions on biomedical circuits and systems
May 18, 2016
Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuro...
IEEE transactions on biomedical circuits and systems
May 18, 2016
Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative ta...
IEEE transactions on biomedical circuits and systems
May 17, 2016
Artificial synaptic devices implemented by emerging post-CMOS non-volatile memory technologies such as Resistive RAM (RRAM) have made great progress recently. However, it is still a big challenge to fabricate stable and controllable multilevel RRAM. ...
IEEE transactions on biomedical circuits and systems
Oct 6, 2015
The cerebellum plays a critical role for sensorimotor control and learning. However, dysmetria or delays in movements' onsets consequent to damages in cerebellum cannot be cured completely at the moment. Neuroprosthesis is an emerging technology that...
IEEE transactions on biomedical circuits and systems
Apr 22, 2015
We have added a simplified neuromorphic model of Spike Time Dependent Plasticity (STDP) to the previously described Synapto-dendritic Kernel Adapting Neuron (SKAN), a hardware efficient neuron model capable of learning spatio-temporal spike patterns....
IEEE transactions on biomedical circuits and systems
Apr 14, 2015
Spin-transfer torque magnetic memory (STT-MRAM) is currently under intense academic and industrial development, since it features non-volatility, high write and read speed and high endurance. In this work, we show that when used in a non-conventional...
IEEE transactions on biomedical circuits and systems
Jun 1, 2025
Cognitive navigation, a high-level and crucial function for organisms' survival in nature, enables autonomous exploration and navigation within the environment. However, most existing works for bio-inspired navigation are implemented with non-neuromo...
IEEE transactions on biomedical circuits and systems
Jun 1, 2025
Bio-inspired neuromorphic hardware with learning ability is highly promising to achieve human-like intelligence, particularly in terms of high energy efficiency and strong environmental adaptability. Though many customized prototypes have demonstrate...
IEEE transactions on biomedical circuits and systems
Jun 1, 2025
This article proposes an analog neuromorphic system that enhances symmetry, linearity, and endurance by using a high-precision current readout circuit for multi-bit nonvolatile electro-chemical random-access memory (ECRAM). For on-chip training and i...
IEEE transactions on biomedical circuits and systems
Jun 1, 2025
Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Brain-Machine Interfaces (BMIs) to improve portability and privacy and maximize battery life. However,...