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Effective Dimensionality Reduction for Visualizing Neural Dynamics by Laplacian Eigenmaps.

Neural computation
With the development of neural recording technology, it has become possible to collect activities from hundreds or even thousands of neurons simultaneously. Visualization of neural population dynamics can help neuroscientists analyze large-scale neur...

All-optical spiking neurosynaptic networks with self-learning capabilities.

Nature
Software implementations of brain-inspired computing underlie many important computational tasks, from image processing to speech recognition, artificial intelligence and deep learning applications. Yet, unlike real neural tissue, traditional computi...

A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network.

Computational intelligence and neuroscience
In this article, we propose to design a new modular architecture for a self-organizing map (SOM) neural network. The proposed approach, called systolic-SOM (SSOM), is based on the use of a generic model inspired by a systolic movement. This model is ...

Scalable Digital Neuromorphic Architecture for Large-Scale Biophysically Meaningful Neural Network With Multi-Compartment Neurons.

IEEE transactions on neural networks and learning systems
Multicompartment emulation is an essential step to enhance the biological realism of neuromorphic systems and to further understand the computational power of neurons. In this paper, we present a hardware efficient, scalable, and real-time computing ...

In-home and remote use of robotic body surrogates by people with profound motor deficits.

PloS one
By controlling robots comparable to the human body, people with profound motor deficits could potentially perform a variety of physical tasks for themselves, improving their quality of life. The extent to which this is achievable has been unclear due...

Compact Hardware Synthesis of Stochastic Spiking Neural Networks.

International journal of neural systems
Spiking neural networks (SNN) are able to emulate real neural behavior with high confidence due to their bio-inspired nature. Many designs have been proposed for the implementation of SNN in hardware, although the realization of high-density and biol...

qTorch: The quantum tensor contraction handler.

PloS one
Classical simulation of quantum computation is necessary for studying the numerical behavior of quantum algorithms, as there does not yet exist a large viable quantum computer on which to perform numerical tests. Tensor network (TN) contraction is an...

New discretization method applied to NBV problem: Semioctree.

PloS one
This paper presents a discretization methodology applied to the NBV (Next Best View) problem, which consists of determining the heuristical best position of the next scan. This new methodology is a hybrid process between a homogenous voxelization and...