Mohammed Arozullah

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Summary form only given. The authors present a number of neural network architectures for the detection and localization of multiple targets in a scene corrupted by background noise and clutter. This scene may be obtained as the output of a staring or a scanning sensor array. The problem is to detect the presence and fix the location of multiple targets in(More)
A neural network data compression method is presented. This network accepts a large amount of image or text data, compresses it for storage or transmission, and subsequently restores it when desired. A new training method, referred to as the Nested Training Algorithm (NTA), that reduces the training time considerably is presented. Analytical results are(More)
Many techniques have been developed for image compression. An efficient image compression technique promises to give high compression ratio, maintaining the quality of the image. The paper proposes an image compression technique which combines both Artificial Neural Networks and Wavelet theory to optimize the compression ratio and peak signal to noise(More)
Timed Efficient Stream Loss-tolerant Authentication (TESLA) and digital signature are security implementations of broadcast authentication in Wireless Sensor Networks (WSNs). Both approaches, however, are considered vulnerable to DoS attacks. Encountering this attack requires a scheme that addresses two security measures: prevention and detection.. This(More)