CMOS image sensors have become very popular in low cost imaging devices. In order to realize images of high quality, the image sensors need to have a high resolution, be able to achieve a high Signal-to-Noise ratio (SNR) and have a wide dynamic range. To increase the spatial resolution of the image sensors, the pixel size has been scaling down allowing integration of more pixels in a given die ...

Image compression technique is used to reduce the number of its required in representing image, which helps to reduce the storage space and transmission cost. In the present research work back propagation neural network training algorithm has been used. Back propagation neural network algorithm helps to increase the performance of the system and to decrease the convergence time for the training...

Vision is fast and efficient. A novel natural scene can be categorized (e.g. does it contain an animal, a vehicle?) by human observers in less than 150 ms, and with minimal attentional resources. This ability still holds under strong backward masking conditions. In fact, with a stimulus onset asynchrony of about 30 ms (the time between the scene and mask onset), the first 30 ms of selective beh...

In this study, the method to apply the feed forward neural networks with two different numbers of hidden layers for harmonic detection process in active filter are described. We have simulated the distorted wave including 5th, 7th, 11th, 13th harmonics and used them for training of the neural networks. The distorted wave including up to 25th harmonics were prepared for testing of the neural net...

The most common approach to generating dense optical ow elds embeds the intensity constancy constraint within a multi-resolution framework using a Laplacian pyramid. Such a framework, in which motion estimates at one scale are used to seed more accurate estimation at ner resolutions, has the potential ability to capture large motions, reducing the likelihood of aliasing. This approach, however,...

"Feed-forward" is a technique that encourages families to imagine the pattern of their relationships at some future point in time. Questions about the future, in conjunction with positive connotation, put families in a metaposition to their own dilemmas and thus facilitate change by opening up new solutions for old problems.

Recent research has focused on feed-forward networks with complex weights and activation values such as GK92, Hir92b, Hir92a, Hir93]. This paper extends this formalism to feed-forward networks with weight and activation values taken from a Cliiord algebra (see also PB92, PB94b]). A Cliiord algebra is a multi-dimensional generalization of the complex numbers and the Quaternions. Essentially a Cl...

The class of adaptive systems known as Artificial Neural Networks (ANN) was motivated by the amazing parallel processing capabilities of biological brains (especially the human brain). The main driving force was to re-create these abilities by constructing artificial models of the biological neuron. The power of biological neural structures stems from the enormous number of highly interconnecte...

The lobula giant movement detector (LGMD) is an identified neuron in the locust visual system that responds preferentially to objects approaching on a collision course with the animal. For such looming stimuli, the LGMD firing rate gradually increases, peaks, and decays toward the end of approach. The LGMD receives both excitatory and feed-forward inhibitory inputs on distinct branches of its d...

Multiplayer perceptrons or feed-forward networks are generally trained to represent functions or many-to-one (m-o) mappings. This creates a problem if the training data exhibits the property of many-to-many or almost many-many valued-ness because the model, which generated the data, was many-to-many. Therefore in this paper a modified feed-forward network and training algorithm is considered to...