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Unattended ground sensors (UGS) are widely used for persistent, surveillance that detects potential threats from intruders without generating false alarms. Battery life is the limiting factor for solutions using digital processing. A 40nW subthreshold analog CMOS (complementary metal oxide semiconductor) chip is fabricated and tested, that wakes up a threat classifying stage. Subthreshold circuits...
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural...
This paper presents a general method of parameter estimation for large-scale non-linear dynamic models a with particular focus on parameter estimation for spike-in, spike-out neural models. The aim is to provide a convex optimization algorithm for tuning parameters of such a model which enables solving large-scale estimation problem in a linear time. Parameter estimation for a single layer neural...
One of the frontier research of neuroscience focuses on replacing the damaged human Hippocampus regions with a prosthetic device replicating Hippocampus neural functionality. Since neural cognition in general and memory formation in particular are the result of neural processing in multiple layers of neural circuitries, it is crucial to develop neural models mimicking the same topology principals...
Linear model for synapse temporal dynamics and learning algorithm for synaptic adaptation in spiking neural networks are presented. The proposed linear model substantially simplifies analysis and training of spiking neural networks, meanwhile accurately models facilitation and depression dynamics in synapse. The learning rule is biologically plausible and is capable of simultaneously adjusting both...
This paper presents a simplified nonlinear model for Dynamic Synapse Neural Network (DSNN) which is based on nonlinear dynamics of neurons in the hippocampus, using a recurrent neural network. The proposed model will be utilized in place of DSNN for various applications which require simpler implementation and faster training, maintaining the same performance as a nonlinear system model, classifier,...
In this paper, a sensor fusion technique with enhanced performance in assets' protection is introduced. The presented fusion technique models activity dynamics in the protected area by combining acoustic, seismic and vibration sensors outputs. The proposed algorithm learns underlying normal activities in the protected area; and detects abnormal activities — possible threat using sensor outputs. The...
Discrete Synapse Recurrent Neural Network (DSRNN) using fully Recurrent Neural Network (RNN) structure and Extended Kalman Filter (EKF) algorithm for its training is improved with time-varying delay in its recurrent connection. An additional shadowing network is employed and learned to choose appropriate time delays at the right time in order to increase the memory depth inside the recurrent connection...
The main focus of this paper is to introduce a new supervised learning algorithm for spiking neural networks. The learning algorithm minimizes the overall differences between spike times of target and test spike trains by utilizing a new quantitative similarity measure which has been defined in this work. The actual membrane potential of a post-synaptic neuron is adjusted at the time of spikes based...
For a lumped nonlinear modeling of the relationship between input and output sequences, Discrete Synapse Recurrent Neural Network (DSRNN) is proposed using fully Recurrent Neural Network (RNN) structure and Extended Kalman Filter (EKF) algorithm for its training. The training process is more efficient and there is less output error and more stability than in the previous study using feedforward networks...
This paper presents a part of a microphone based system installed on a soldier's helmet for the application of localizing a sniper/insurgent attack in the battle space environment to increase situational awareness of the foot soldiers. More specifically, the main focus of the paper is to develop a computational method to determine the optimum number of microphone sensors and their optimum positions...
In this paper we propose a portable and compact system for real-time monitoring/assessing of individuals fatigue under active conditions based on measurements of eyes. Real-time monitoring of fatigue - cognitive, physiological, and physical - can help supervisors and commanders to prudently assign tasks so as to prevent human errors and causalities. The proposed system utilizes a very small camera...
While there are number of guidelines and methods used in practice, there is no standard universally agreed upon system for assessment of pathological voices. Pathological voices are primarily labeled based on the perceptual judgments of specialists, a process that may result in different label(s) being assigned to a given voice sample. This paper focuses on the recognition of five specific pathologies...
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