2003/3

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    Exploitation of Higher Order Moments Increase the Tracking Aircraft by the Extended Alpha-Beta Filter
    (Společnost pro radioelektronické inženýrství, 2003-09) Dostal, Zdenek; Mokris, Igor
    The paper analyzes the possibility of exploitation of higher order moments for increasing the precision of tracking of a flying aircraft by the α-β filter. For tracking of a flying aircraft by the α-β filter the 3rd and 4th order moments in 3D space are used.
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    Compaction Filter as an Optimum Solution for Multirate Subband Coder of Cyclostationary Signals
    (Společnost pro radioelektronické inženýrství, 2003-09) Kula, Daniel
    A consistent theory of optimum subband coding of zero mean wide-sense cyclostationary signals with N-periodic statistics is presented in this paper. Blocked polyphase representation of the analysis and synthesis filter banks is introduced as an effective way of multirate subband coder description. Optimum energy compaction using Nyquist-M process is presented as a solution for maximizing the coding gain of the coder. In two definitions and four theorems the author proves that Nyquist-M filters fulfill necessary and sufficient conditions imposed on subband signals. Results from Matlab simulations are presented to support theoretical conclusions.
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    Hybrid Scheme with Triangulations for Transform Coding
    (Společnost pro radioelektronické inženýrství, 2003-09) Partyk, Martin; Polec, Jaroslav; Kolingerova, Ivana
    Our approach to image region approximation offers a complete scheme consisting of several steps. We separate the encoding of region boundaries from the texture description. The original image is first segmented using an unsupervised segmentation method for color-texture regions. Following polygonal approximation of created regions causes the degradation of region boundaries. The triangulation is then applied to polygons and either all short edges, or all small triangles are filtered out from the triangular mesh. This results in new smaller regions. The encoding and decoding of polygons and triangles is very efficient, because we need to store only the vertices. For texture approximation we use 2D shape independent orthogonal transforms (e.g. DCT II). The texture is encoded with a code similar to JPEG arithmetic code. The encoding scheme proposed in this paper is much faster than latest approaches with polygonal approximation. We present the two triangulation algorithms - constrained greedy (CGT) and constrained Delaunay triangulation (CDT). Both CGT and CDT provide similar results.
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    Noise Figure Measurement of Highly Mismatched DUT
    (Společnost pro radioelektronické inženýrství, 2003-09) Sokol, Vratislav; Hoffmann, Karel; Vajtr, Jiri
    A device mismatch seriously degrades the accuracy of its noise figure characterization. A new second stage correction technique for highly mismatched device under test is proposed and compared to the standard technique. The presented method is based on additional vector measurement. It takes into account measuring receiver noise figure dependence on the DUT output mismatch besides an available gain correction. Significant accuracy improvement of measured data and decreased error variation is demonstrated. The suggested method is in principle able to eliminate all systematic errors in noise figure measurement.
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    EEG Signal Classification: Introduction to the Problem
    (Společnost pro radioelektronické inženýrství, 2003-09) Stastny, Jakub; Sovka, Pavel; Stancak, Andrej
    The contribution describes the design, optimization and verification of the off-line single-trial movement classification system. Four types of movements are used for the classification: the right index finger extension vs. flexion as well as the right shoulder (proximal) vs. right index finger (distal) movement. The classification system utilizes hidden information stored in the characteristic shapes of human brain activity (EEG signal). The great variability of EEG potentials requires using of context information and hence the classifier based on Hidden Markov Models (HMM). The suitable parameterization, model structure as well as training and classification process are suggested on the base of spectral analysis results and experience with the speech recognition. The training and the classification are performed with the disjoint sets of EEG realizations. Classification experiments are performed with 10 randomly chosen sets of EEG realizations. The final average score of the distal/proximal movement classification is 80%; the standard deviation of classification results is 9%. The classification of the extension / flexion gives comparable results.