[PDF] Top 20 A survey on real time processing with spiking neural networks

... neurons. Spiking neural network (SNN) approach in ANNs is more closely related to the biological neurons [7] with information encoding in the form of action potentials called spikes that last for one ... See full document

... a spiking neural network (SNN) for sound localisation based on real sound recorded in a noisy and dynamic environment by a mobile ...interaural time difference ... See full document

... The spiking neural networks, which inherit the parallel mechanism from biological system, are introduced to extract the features of the face ...to spiking neuron based artificial intelligent ... See full document

... training time, andapprehensivelycomprehensibleillustrationof results, neural networks have high acceptance ability for noise acceptance and high accuracy and are preferred indata ...supported ... See full document

... unipolar networks are based on the concept of setting up “weight oscillators” to create a context-sensitive dynamic connectivity map through ...bipolar networks, activity can be perturbed in a single ... See full document

... anti-Hebbian window. This novel learning strategy, demonstrated using an obsta- cle avoidance task, used a conventional Hebbian learning window. However, the SNN could be reconfigured to learn an object tracking task ... See full document

... brained-inspired spiking neural networks (SNNs), which can be applied on visual information processing and speech recognition, is attracting great attention especially when combined with ... See full document

... SNN are the third generation of neural network model. The model uses spikes as a substitute and analyses the pulse coded information (Gerstner, 2001; Gerstner et al., 1993; Gerstner & van Hemmen, 1994; N. ... See full document

... as Spiking Neural Networks- SNNs) , the inputs to each neuron consist of pulse spikes arriving at random , and the values of the spikes incident onto the neurons are the values of the arriving spikes ... See full document

... Spiking neural networks fall into third generation of neural network ...a neural simulation increasing the level of ...of time into their operating ...artificial neural ... See full document

... the spiking neural network still lack of good learning ...the networks have the potential to perform defect classification in terms of better speeds of ...on-line real-time ... See full document

... artificial neural networks that, with advancements in training algorithms and architectures, have cemented themselves as the future of learning and data processing in modern ...current neural ... See full document

... different types of network, their fundamental intrinsic differences would still mean that a direct comparison may not be achievable. Care had to be taken in the design of the systems involved in this experiment as design ... See full document

... same time, block-level synchronization is required among all warps at each point of a task ...execution time of each block is maximized by the number of divergent spike events within each ...order ... See full document

... the winner neurons (first spiking neurons) are increased while other neurons suffer a small weight reduction value. Tests showed that depressing the weights of the non firing neurons decrease the amount of noise ... See full document

... Homeostasis is a property of a system to maintain relatively stable equilibrium when subjected to continuous change. The mechanisms that monitor excitation and maintain the func- tional properties of neurons are by ... See full document

... the real-time computing system is deadline. In a real-time control system the packets which are transmitted from source node should arrive at desti- nation before deadline for guaranteeing the ... See full document

... some real time pattern. The presented model used the spiking neuron based PCA approach to perform the real time pattern detection over the ...the real time pattern image ... See full document

... Vikramaditya Dangi et.al. [15] Propose the way to implement an intelligent traffic controller using real time image processing techniques. The image sequences from a camera are analyzed using various ... See full document

... The tumours are placed in a 3D Finite-Difference Time-Domain (FDTD) model. The FDTD model has a 0.5 mm cubic grid resolution and the backscattered signals were generated through a Total- Field/Scattered-Field ... See full document