Search for dissertations about: "low rate quantization"
Showing result 1 - 5 of 16 swedish dissertations containing the words low rate quantization.
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1. Towards Low-Complexity Vector Quantization
Abstract : This thesis is about constructing low-complexity, yet high-performance, vector quantizers (VQs) for 'real-world' sources. Knowledge concerning the source is extracted from a finite training set. In contrast with conventional VQ design procedures, we use the training set to estimate a statistical model for the source. READ MORE
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2. Trellis Source Coding Methods for Low Rates and Short Blocks
Abstract : Trellis quantization is a finite state machine based method for data compression. It is mainly applied to quantizing noise-like sources. In this thesis new trellis codes suitable for low rate quantization are derived. READ MORE
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3. Distribution Preserving Quantization
Abstract : In the lossy coding of perceptually relevant signals, such as sound and images, the ultimate goal is to achieve good perceived quality of the reconstructed signal, under a constraint on the bit-rate. Conventional methodologies focus either on a rate-distortion optimization or on the preservation of signal features. READ MORE
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4. Massive Multi-Antenna Communications with Low-Resolution Data Converters
Abstract : Massive multi-user (MU) multiple-input multiple-output (MIMO) will be a core technology in future cellular communication systems. In massive MU-MIMO systems, the number of antennas at the base station (BS) is scaled up by several orders of magnitude compared to traditional multi-antenna systems with the goals of enabling large gains in capacity and energy efficiency. READ MORE
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5. Quantization, Perception and Speech Coding
Abstract : This thesis is about compression of speech signals, a research area known as speech coding. The aim of a speech coder is to provide efficient digital representations of speech signals, required in digital transmission and storage systems. Contemporary speech coding algorithms typically separate the speech signal into sets of parameters. READ MORE