The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper investigates signal predictive quantization subject to channel loss. It uses the analysis and design tools of H∞ optimal filtering of discrete-time Markov jump linear system to obtain an optimal predictor for a signal predictive quantization system with channel loss. A linear matrix inequality (LMI) based design method is derived to design the predictor that minimizes the variance of the...
This paper is concerned with signal predictive quantization with channel loss. It uses the analysis and design tools of H2 optimal filtering of discrete-time Markov jump linear system to obtain an optimal predictor for a signal predictive quantization system with channel loss. An LMI based design method is derived to design the predictor that minimizes the variance of the reconstruction error subject...
This paper investigates optimal signal predictive quantization in the presence of source model uncertainties. It uses polytopic system model to represent the uncertainties in source signal and uses the recent results on robust filtering to obtain a robust H∞ optimal design of signal predictor. Results of computational study is presented to demonstrate the advantages of the obtained design.
This paper is concerned with the design of signal predictor in oversampled signal predictive subband coding. Spectral analysis of the prediction error system is used to derive an H2 optimization formulation of the design problem, and an LMI based method is obtained to design the H2 optimal signal predictor that minimizes the variance of quantizer input signals. Simulation examples are presented to...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.