September 2003, Volume 12, Number 3
J. Dobes, J. Michal
Using the Variable-Length Arithmetic for an Accurate Poles-Zeros Analysis
In the paper, a reduction algorithm for transforming the general eigenvalue problem to the standard one is presented for both classical full-matrix methods and a sparse-matrix technique appropriate for large-scale circuits. An optimal pivoting strategy for the two methods is proposed to increase the precision of the computations. The accuracy of the algorithms is furthermore increased using longer numerical data. First, a ORQJ.GRXEOH precision sparse algorithm is compared with the GRXEOH precision sparse and full-matrix ones. Finally, the application of a suitable multiple-precision arithmetic library is evaluated.
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Filters with Multi-Loop Feedback Structure in Current Mode
Universal multifunctional (low-pass, high-pass, band-pass, band-reject and all-pass) nth-order active RC filters in current mode are presented in this paper. The filters are based on several multi-loop feedback and state-variable structures. Their modification and implementation using multi-output transconductors (OTA) and current followers are given.
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V. Sokol, K. Hoffmann, J. Vajtr
Noise Figure Measurement of Highly Mismatched DUT
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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B. Taha-Ahmed, M. Calvo-Ramon, L. de Haro-Ariet
On the UMTS Downlink Capacity in (Open Rural and Countryside) Zone Near Deep Space Network (DSN) Installations
The UMTS macrocell downlink capacity is evaluated for macrocells that operate at the same frequency as the Deep Space Network (DSN) and that are nearby the DSN installations. It has been found that the cell capacity is not affected when the distance between the DSN installations and the macrocell is more than 21 km. For lower distance, the effect is high and the downlink vanishes at a distance less than 2 km when the microcell radius is 1 km. Near the DSN installation, the macrocell radius has to be 1 km or less.
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B. Taha-Ahmed, M. Calvo-Ramon, L. de Haro-Ariet
W-CDMA Uplink Capacity and Interference Statistics of a LongGroove-Shaped Road Microcells Using A Hybrid Propagation Model
The uplink capacity and the interference statistics of the sectors of a long groove-shaped road W-CDMA microcell are studied. A model of 9 microcells in a groove-shaped road is used to analyze the uplink. A hybrid model for the propagation is used in the analysis. The capacity and the interference statistics of the cell are studied for different sector ranges, different specific attenuation factors, different antenna side lobe levels and different bend losses.
- CHO, H. S., CHUNG, M. Y., KANG, S. H., SUNG, D. K. Performance analysis of cross- and cigar shaped urban microcells considering user mobility characteristics. IEEE Transactions on Vehicular Technology. 2000, vol. 49, no. 1, p 105 - 115.
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Compaction Filter as an Optimum Solution for Multirate Subband Coder of Cyclostationary Signals
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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Preemphasis Influence on Harmonic Speech Model with Autoregressive Parameterization
Autoregressive speech parameterization with and without preemphasis is discussed for the source-filter model and the harmonic model. Quality of synthetic speech is compared for the harmonic speech model using autoregressive parameterization without preemphasis, with constant and adaptive preemphasis. Experimental results are evaluated by the RMS log spectral measure between the smoothed spectra of original and synthesized male, female, and childish speech sampled at 8 kHz and 16 kHz. Although the harmonic model is used, the benefit of the adaptive preemphasis could be valid for the source-filter model, as well.
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J. Stastny, P. Sovka
The contribution addresses the cross-language experiment. The aim was to test the possibility of the conversion French phoneme models into Czech ones. This model conversion uses the Hidden Markov Models (HMM) classification procedure. The first step consists of the iterative mapping of French models to Czech ones. The mapping is given by the analysis the confusion matrix. The second step is the Baum-Welch re-estimation resulting in the final models for Czech language. Despite of the differences between French and Czech languages the final recognition score reaches 64% for the phoneme recognition and 74% for digit recognition. Relatively low recognition accuracy is caused by the inadequate noise model. The experiences gained with the cross-language experiment were utilized for the classification of simple human body movements. The solution of this problem and results are described in the second part of this contribution under the title EEG Signals Classification-Introduction to the Problem.
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M. Partyk, J. Polec, I. Kolingerova
Hybrid Scheme with Triangulations for Transform Coding
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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Mixed Noise Suppression in Color Images by Signal-Dependent LMS L-Filters
The paper is devoted to the signal-dependent (SD) design of adaptive LMS L-filters with marginal data ordering for color images. The same stem of SD processing of noised grayscale images was applied on noisy color images. Component-wise and multichannel modifications of SD LMS L-filter in R'G'B' (gamma corrected RGB signals) color space were developed. Both modifications for filtering two-dimensional static color images degraded by mixed noise consisting of additive Gaussian white noise and impulsive noise were used. Moreover, single-channel spatial impulse detectors as detectors of impulses and details were used, too. Considering experimental results, SD modifications of L-filters for noisy color images can be concluded to yield the best results.
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J. Stastny, P. Sovka, A. Stancak
EEG Signal Classification: Introduction to the Problem
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.
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Z. Dostal, I. Mokris
Exploitation of Higher Order Moments Increase the Tracking Aircraft by the Extended Alpha-Beta Filter
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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