Essays about: "Decoding."
Showing result 11 - 15 of 238 essays containing the word Decoding..
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11. Utilizing Neural Networks To Adaptively Demodulate And Decode Signals In An Impulsive Environment
University essay from Uppsala universitet/Avdelningen för datalogiAbstract : Electromagnetic disturbance can be detrimental to the performance of a radio communication system, and in today’s society where more and more electronic devices are present in our everyday life it is increasingly vital to consider man-made interference. A communication system can take into consideration the noise characteristics and by doing so will excel in such areas, however, this follows that the algorithms utilized in such systems are more computationally complex and are therefore slow. READ MORE
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12. Comparison of Output Decoding Techniques for Spiking Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Spiking Neural Networks (SNNs) hold significant potential due to their high energy efficiency when implemented on specialized hardware. Central to SNNs is the translation of sequences of spike events to concrete outputs, like class predictions. READ MORE
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13. A Satirist's Right to Criticise : Satire in "It's Always Sunny in Philadelphia": A Genre and Audience Reception Analysis
University essay from Malmö universitet/Institutionen för konst, kultur och kommunikation (K3)Abstract : This thesis explores the utilisation of satire within the television series It's Always Sunny in Philadelphia. Employing Stuart Hall's encoding/decoding model as a theoretical framework, this study delves into the complexities of how satire is constructed, received, and interpreted by viewers. READ MORE
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14. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. READ MORE
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15. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. READ MORE