https://ieeexplore.ieee.org/document/8471012This paper presents a survey of the currently available hardware designs for implementation of the human cortex inspired algorithm, Hierarchical Temporal Memory (HTM). In this review, we focus on the state of the art advances of memristive HTM implementation and related HTM applications. With the advent of edge computing, HTM can be a potential algorithm to implement on-chip near sensor data processing. The comparison of analog memristive circuit implementations with the digital and mixed-signal solutions are provided. The advantages of memristive HTM over digital implementations against performance metrics such as processing speed, reduced on-chip area and power dissipation are discuss...
https://arxiv.org/abs/1803.05131Hierarchical temporal memory (HTM) is a neuromorphic algorithm that ...
Significant interest has been placed on developing systems based on the memristor, which was physica...
In this Review, memristors are examined from the frameworks of both von Neumann and neuromorphic com...
The authors propose a discrete-level memristive memory design for analogue data processing in hardwa...
Ideally, a memristor has infinite memory states making it a promising device as an analog memory. Ho...
The on-chip implementation of learning algorithms would accelerate the training of neural networks i...
This article investigates hardware implementation of hierarchical temporal memory (HTM), a brain-ins...
As a software framework, Hierarchical Temporal Memory (HTM) has been developed to perform the brain&...
Analog switching memristive devices can be used as part of the acceleration block of Neural Network...
Analog compute schemes and compute-in-memory (CIM) have emerged in an effort to reduce the increasin...
This book covers a range of models, circuits and systems built with memristor devices and networks i...
Analogue in-memory computing and brain-inspired computing based on the emerging memory technology ...
Recent discovery of the memristor has sparked a new wave of enthusiasm and optimism in revolutionisi...
In the past decades, the computing capability has shown an exponential growth trend, which is observ...
Memristor or RRAM (Resistive Random-Access Memory) based crossbar array architecture is considered a...
https://arxiv.org/abs/1803.05131Hierarchical temporal memory (HTM) is a neuromorphic algorithm that ...
Significant interest has been placed on developing systems based on the memristor, which was physica...
In this Review, memristors are examined from the frameworks of both von Neumann and neuromorphic com...
The authors propose a discrete-level memristive memory design for analogue data processing in hardwa...
Ideally, a memristor has infinite memory states making it a promising device as an analog memory. Ho...
The on-chip implementation of learning algorithms would accelerate the training of neural networks i...
This article investigates hardware implementation of hierarchical temporal memory (HTM), a brain-ins...
As a software framework, Hierarchical Temporal Memory (HTM) has been developed to perform the brain&...
Analog switching memristive devices can be used as part of the acceleration block of Neural Network...
Analog compute schemes and compute-in-memory (CIM) have emerged in an effort to reduce the increasin...
This book covers a range of models, circuits and systems built with memristor devices and networks i...
Analogue in-memory computing and brain-inspired computing based on the emerging memory technology ...
Recent discovery of the memristor has sparked a new wave of enthusiasm and optimism in revolutionisi...
In the past decades, the computing capability has shown an exponential growth trend, which is observ...
Memristor or RRAM (Resistive Random-Access Memory) based crossbar array architecture is considered a...
https://arxiv.org/abs/1803.05131Hierarchical temporal memory (HTM) is a neuromorphic algorithm that ...
Significant interest has been placed on developing systems based on the memristor, which was physica...
In this Review, memristors are examined from the frameworks of both von Neumann and neuromorphic com...