Submittedinpartialfulfillmentof thecourserequirementsfor " NeuralNetworks " ECEN5733 May2000

Next Word Prediction is additionally called Language Modeling. It the undertaking of predicting what word comes straightaway. one major assignments NLP and has numerous applications. Attempting to make model utilizing nietzsche default text record which will foresee clients sentence after composed 40 letters, comprehend letters anticipate impending top 10 words RNN neural organization be execut...

Real-codedgenetic algorithms on a parallel architecture are applied to optimize the synaptic couplings of a Cellular Neural Network for specific greyscale image processing tasks. Using supervised learning information in the jitnessfinction, we propose the Genetic Algorithm as a general training methodfor Cellular Neural Networks. 01997 Elsevier Science Ltd. Keywords-Cellular neuralnetworks,Gene...

In the present work, a neural-networks-based system is presented that makes it possible to reduce, when generating edge maps to be used in an object boundary detection problem, the number of edges that are not due to the object itself, but to the background. Starting from a conventional edge detection, the selection is carried out by a neuralnetworks-based classifier, which is trained using exa...

This paper proposes a new electromyogram (EMG) pattern classification method using probabilistic neuralnetworks based on boosting approach [1]. Since the proposed method automatically constructs a suitable classification network from measured EMG signals, there is no need to set the structure of network in advance. To verify the feasibility of the proposed method, phoneme classification experim...

Signature verification is a unique method to identify the person which is used word-wide. To reduce the cost of online verification process, I have utilized the on-line registration and off-line verification process to reduce cost. It utilizes NeuralNetworks to identify the various parameters to identify and train the model system. It has resulted in low cost and accurate off-line model for ver...

This paper proposes a layered modular architecture to adaptively perform data mining tasks in large sensor networks. The architecture consists in a lower layer which performs data aggregation in a modular fashion and in an upper layer which employs an adaptive local learning technique to extract a prediction model from the aggregated information. The rationale of the approach is that a modular ...