Search for dissertations about: "efficient coding"
Showing result 16 - 20 of 141 swedish dissertations containing the words efficient coding.
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16. Early-Decision Decoding of LDPC Codes
Abstract : Since their rediscovery in 1995, low-density parity-check (LDPC) codes have received wide-spread attention as practical capacity-approaching code candidates. It has been shown that the class of codes can perform arbitrarily close to the channel capacity, and LDPC codes are also used or suggested for a number of important current and future communication standards. READ MORE
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17. Efficient Software Implementation of Stream Programs
Abstract : The way we use computers and mobile phones today requires large amounts of processing of data streams. Examples include digital signal processing for wireless transmission, audio and video coding for recording and watching videos, and noise reduction for the phone calls. READ MORE
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18. Preferential Coding for Mobile Multimedia Services
Abstract : Different parts of source encoded multimedia streams such as those associated with standard image or video formats possess different levels of importance with respect to their contribution to the quality of the reconstructed image or video. This unequal importance among data within a codestream gives rise to preferential treatment of the more significant parts of the codestream compared to the less important parts. READ MORE
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19. On Secure and Sequential Source Coding
Abstract : Secure source coding is an important research area in recent years as it deals with the problem of transmitting sensitive information over insecure channels while protecting it from unauthorized access. This is particularly relevant in the context of modern communication systems where the data transmitted is often sensitive in nature and the threat of eavesdropping or data breaches is high. READ MORE
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20. Reliable and Efficient Distributed Machine Learning
Abstract : With the ever-increasing penetration and proliferation of various smart Internet of Things (IoT) applications, machine learning (ML) is envisioned to be a key technique for big-data-driven modelling and analysis. Since massive data generated from these IoT devices are commonly collected and stored in a distributed manner, ML at the networks, e.g. READ MORE