236 research outputs found
Estimation and control with bounded data uncertainties
AbstractThe paper describes estimation and control strategies for models with bounded data uncertainties. We shall refer to them as BDU estimation and BDU control methods, for brevity. They are based on constrained game-type formulations that allow the designer to explicitly incorporate into the problem statement a priori information about bounds on the sizes of the uncertainties. In this way, the effect of uncertainties is not unnecessarily over-emphasized beyond what is implied by the a priori bounds; consequently, overly conservative designs, as well as overly sensitive designs, are avoided. A feature of these new formulations is that geometric insights and recursive techniques, which are widely known and appreciated for classical quadratic-cost designs, can also be pursued in this new framework. Also, algorithms for computing the optimal solutions with the same computational effort as standard least-squares solutions exist, thus making the new formulations attractive for practical use. Moreover, the framework is broad enough to encompass applications across several disciplines, not just estimation and control. Examples will be given of a quadratic control design, an H∞ control design, a total-least-square design, image restoration, image separation, and co-channel interference cancellation. A major theme in this paper is the emphasis on geometric and linear algebraic arguments, which lead to useful insights about the nature of the new formulations. Despite the interesting results that will be discussed, several issues remain open and indicate potential future developments; these will be briefly discussed
Adaptive differential pulse-coded modulation with exponential tracking
This paper first investigates a companded differential pulse-coded modulator and. derives an expression for its SNR performance. Analysis and simulations show that, the coder has superior SNR and dynamic range performance over other coders of similar complexity. The companded modulator is then extended to an adaptive differential pulse-coded modulator with high SNR and dynamic range performance, and it is shown to be BIBO stable
Adaptive predictive power control for the uplink channel in DS-CDMA cellular systems
In this paper, we analyze the conventional closed-loop power-control system. We explain that the system behaves essentially as a companded delta modulator and then derive an expression for the power-control error in terms of the channel fading, which suggests methods for reducing the error variance. This is achieved by using a prediction technique for estimating the channel-power fading profile. The prediction module is combined with several proposed schemes for closed-loop power control. The resulting architectures are shown to result in improved performance in simulations
Adaptive differential pulse-coded modulation with exponential tracking
This paper first investigates a companded differential pulse-coded modulator and. derives an expression for its SNR performance. Analysis and simulations show that, the coder has superior SNR and dynamic range performance over other coders of similar complexity. The companded modulator is then extended to an adaptive differential pulse-coded modulator with high SNR and dynamic range performance, and it is shown to be BIBO stable
Effects of short term feeding of some marine microalgae on the microbial profile associated with Dicentrarchus labrax post larvae
AbstractThis study investigates the microbial profile and antimicrobial activity of four marine microalgae species, Tetraselmis chuii, Nannochloropsis salina, Isochrysis galbana and Chlorella salina used in aquaculture of Dicentrarchus labrax in the post larval stage to estimate which was the best algal species that could be used as a green water technique and achieving the maximum rate of growth and survival of D. labrax post larvae. The results represented a significant increase in the length and width of D. labrax at p<0.05 recorded in the case of enrichment with I. galbana followed by N. salina, and the most weight was recorded in the case of N. salina as compared with the control. Significant increase in percentage of survival of D. labrax was recorded in the case of C. salina and T. chuii (70% and 60.1%, respectively) as compared with the control (22%). The antibacterial activity (AU) of the different microalgal ethanolic extracts against fish indicator pathogens was determined. The results indicated that the ethanolic extracts of C. salina and T. chuii have the most positive records against the fish indicator pathogens (Escherichia coli, Pseudomonas aeruginosa, Vibrio damsela, Vibrio fluvialis and Aeromonas hydrophila). The current study was extended to determine the GC–MS of ethanolic extract of C. salina and T. chuii. The main constituents detected in the ethanolic extract were organic acids like hexadecanoic acid, octadecanoic acid, and an acyclic diterpene alcohol like phytol
Adaptive Multi-Input Multi-Output Fading Channel Equalization using Kalman Estimation
his paper addresses the problem of adaptive channel tracking and equalization for multi-input multi-output (MIMO) time-variant frequency-selective channels. A finite-length minimum-mean-squared-error decision-feedback equalizer (MMSE-DFE) performs the equalization task, while a Kalman filter tracks the MIMO channel, which models the corrupting effects of inter-symbol interference (ISI), inter-user interference (IUI), and noise. The Kalman tracking is aided by previous hard decisions produced by the DFE, with a decision delay ~ > 0, which causes the Kalman filter to track the channel with a delay. A channel prediction module bridges the time gap between the channel estimates produced by the Kalman filter and those needed for the DFE adaptation. The proposed algorithm offers good tracking behavior for multi-user fading ISI channels at the expense of higher complexity. Download the full articl
A Probabilistic Multimedia Retrieval Model and its Evaluation
We present a probabilistic model for the retrieval of multimodal documents. The model is based on Bayesian decision theory and combines models for text-based search with models for visual search. The textual model is based on the language modelling approach to text retrieval, and the visual information is modelled as a mixture of Gaussian densities. Both models have proved successful on various standard retrieval tasks. We evaluate the multimodal model on the search task of TREC′s video track. We found that the disclosure of video material based on visual information only is still too difficult. Even with purely visual information needs, text-based retrieval still outperforms visual approaches. The probabilistic model is useful for text, visual, and multimedia retrieval. Unfortunately, simplifying assumptions that reduce its computational complexity degrade retrieval effectiveness. Regarding the question whether the model can effectively combine information from different modalities, we conclude that whenever both modalities yield reasonable scores, a combined run outperforms the individual runs
Schur functions and their realizations in the slice hyperholomorphic setting
we start the study of Schur analysis in the quaternionic setting using the
theory of slice hyperholomorphic functions. The novelty of our approach is that
slice hyperholomorphic functions allows to write realizations in terms of a
suitable resolvent, the so called S-resolvent operator and to extend several
results that hold in the complex case to the quaternionic case. We discuss
reproducing kernels, positive definite functions in this setting and we show
how they can be obtained in our setting using the extension operator and the
slice regular product. We define Schur multipliers, and find their co-isometric
realization in terms of the associated de Branges-Rovnyak space
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