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This paper presents a hardware based implementation of a biologically-faithful astrocyte-based selfrepairing mechanism for Spiking Neural Networks. Spiking Astrocyte-neuron Networks (SANNs) are a new computing paradigm which capture the key mechanisms of how the human brain performs repairs. Using SANN in hardware affords the potential for realizing computing architecture that can self-repair. This...
The human brain is structured with the capacity to repair itself. This plasticity of the brain has motivated researchers to develop systems which have similar capabilities of fault tolerance and self-repair. Recent research findings have proven that interactions between astrocytes and neurons can actuate brain-like self-repair in a bidirectionally coupled astrocyte-neuron system. This paper presents...
Hardware faults are becoming more frequent due to geometric scaling, reducing the reliability and lifespan of devices. Current fault-tolerant approaches use redundancy or a central controller to detect and/or repair faults. However, these methods are also susceptible to faults. Astrocytes have been shown to facilitate biological self-repair in silent or near silent neurons in the brain by increasing...
A self-repairing robot utilising a spiking astrocyte-neuron network is presented in this paper. It uses the output spike frequency of neurons to control the motor speed and robot activation. A software model of the astrocyte-neuron network previously demonstrated self-detection of faults and its self-repairing capability. In this paper the application demonstrator of mobile robotics is employed to...
Scalability is a key challenge for digital spiking neural networks (SNN) in hardware. This paper proposes an efficient neuron architecture (ENA) to reduce the silicon area occupied by neurons. As the computation resource (e.g. DSP in FPGAs) is limited for hardware SNNs, the proposed ENA employs a sharing mechanism of computing component at two levels (synapse and neuron) to reduce the occupied resources...
A Self-rePAiring spiking Neural NEtwoRk (SPANNER) hardware architecture is presented in this paper. It is based on a software model of an astrocyte-neuron network which previously demonstrated the ability to self-detect faults and self-repair autonomously. Experimental results in this paper show that when faults occur at the synapse, remaining healthy synapses of the same neuron are enhanced by the...
In this paper, a novel technique for human daily motion analysis and recognition is proposed. The technique is based on the use of inertial sensors, and integrates a longest common subsequences (LCSS) algorithm as the kernel function for support vector machines (SVM), which measures the similarity of human daily motion time-series. In our system, we use the wearable motion capture system to obtain...
Sleep apnea contributes to a variety of health threatening problems. However, there is a extremely low public and medical awareness of this disease. In order to identify sleep apnea/hyopnea, some effective features have been extracted from ECG signal, PPG signal and EEG signal. In this work, a novel combined of features characterizing physiological signals for monitoring epochs of sleep apnea is presented...
A key requirement for modern large scale neuromorphic systems is the ability to detect and diagnose faults and to explore self-correction strategies. In particular, to perform this under area-constraints which meet scalability requirements of large neuromorphic systems. A bio-inspired online fault detection and self-correction mechanism for neuro-inspired PID controllers is presented in this paper...
Modern Networks-on-Chip (NoC) have the capability to tolerate and adapt to the faults and failures in the hardware. Monitoring and debugging is a real challenge due to the NoC system complexity and large scale size. A key requirement is an evaluation and benchmarking mechanism to quantitatively analyse a NoC system's fault tolerant capability. A novel monitoring mechanism is proposed to evaluate the...
A key requirement for modern Networks-on-Chip (NoC) is the ability to detect and diagnose faults and failures. A novel approach is proposed which addresses the challenge of fault detection using an online mechanism. The approach minimises online intrusion by employing dynamic rates of testing to maximize NoC throughput while still ensuring sufficient testing. This is achieved using a novel Monitor...
In order to ensure space manipulator operates safely and reliably, dependable locking and fixing is necessary before launching. Thus, locking and fixing of space manipulator is extremely important. Optimized number and position of locked points are needed while locking and fixing. Based on the number of manipulator's locked points and position's disposal method and finite theory, the system first-order...
In this paper, properties of overshoot and undershoot as functions of circuit parameters are investigated. We establish transient analysis circuit model for the test conditions of signal generator, then analyze the overshoot and undershoot by this model, and point out they are mainly related to the distributed inductance, resistance, and the loading capacitance of circuits. Three comparative tests...
In this paper, a novel approach for digital image chaotic communication via FPGA embedded Ethernet transmission is proposed. Based on Euler algorithm and variable ratio expansion transformation, by C language programming under the Linux operating system, the continuous time 8-scroll Chua system is converted to the discrete sequence used to encrypt and decrypt image on the FPGA-based platform. According...
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