نتایج جستجو برای: nn implementation
تعداد نتایج: 372770 فیلتر نتایج به سال:
Under unbalanced supply condition low order harmonics will appear at the input and output terminals of the PWM AC to DC converter. Based on the positive and negative sequence components, an unbalanced transfer matrix in terms of the input phase voltages is derived. An on-line method using a neural network (NN) is used to implement this transfer matrix. It is shown that by using an additional lo...
Bio-inspired processes are involved more and more in today’s technologies, yet their modelling and implementation tend to be taken away from their original concept because of the limitations of the classical computation paradigm. To address this, [1] introduced systemic computation (SC), a model of interacting systems with natural characteristics, and [2] introduced a modelling platform with a ...
This paper presents a neural network (NN) to recover threedimensional (3D) shape of an object from its multiple view images. The object may contain non-overlapping transparent and opaque surfaces. The challenge is to simultaneously reconstruct the transparent and opaque surfaces given only a limited number of views. By minimizing the pixel error between the output images of this NN and teacher ...
In this paper we propose NNCTPH, a new MapReduce algorithm that is able to build an approximate k-NN graph from large text datasets. The algorithm uses a modified version of Context Triggered Piecewise Hashing to bin the input data into buckets, and uses an exhaustive search inside the buckets to build the graph. It also uses multiple stages to join the different unconnected subgraphs. We exper...
Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation of a multi-input ...
Sammon’s mapping is conventionally used for exploratory data projection, and as such is usually inapplicable for classification. In this paper we apply a neural network (NN) implementation of Sammon’s mapping to classification by extracting an arbitrary number of projections. The projection map and classification accuracy of the mapping are compared with those of the auto-associative NN (AANN),...
This paper presents a novel and fast k-NN classifier that is based on a binary CMM (Correlation Matrix Memory) neural network. A robust encoding method is developed to meet CMM input requirements . A hardware implementation of the CMM is described, which gives over 200 times the speed of a current mid-range workstation, and is scaleable to very large problems. When tested on several benchmarks ...
This The process of estimating the geographical location of sensor nodes, called localization is an important research area in WSN. Accurate localization or tracking of wireless device is a crucial requirement for many emerging location aware systems. Fields of application include search & research, medical care, intelligent transportation, location based billing, security, home automation, ind...
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