The volume 2006

Table of Contents

Herbert PEREMANS, Bertrand FONTAINE: Sonar target localization based on spike coded spectrograms
Abstract  Full Text

Radu DOGARU, Manfred GLESNER, Ronald TETZLAFF: Cellular automata codebooks applied to compact image compression
Abstract  Full Text

Daniela TARNICERIU, Valeriu MUNTEANU, Florin BELDIANU: Frequency content oriented modification of quantization matrix in DCT-based compression
Abstract  Full Text

Daniela COLTUC, Thierry FOURNEL, Jean-Marie BECKER, Yann BOUTANT: An ICA based method for texture recognition
Abstract  Full Text

Ion BOGDAN: Minimizing the error tracking of mobile terminals by Kalman filtering
Abstract  Full Text

Valeriu MUNTEANU, Daniela TARNICERIU: Optimal coding for qualitative sources on noiseless channels
Abstract  Full Text

Radu DOGARU, Gabriel Nicolae COSTACHE, Octavian DUMITRU, Inge GAVAT: A novel feature extraction method for isolated word recognition based on Nested Temporal Averaging
Abstract  Full Text

Viorel NICOLAU, Rustem POPA, Constantin MIHOLCA: Spectral density correction of a signal at frequency variable transformation
Abstract  Full Text

Mihai GAVRILAS, Ovidiu IVANOV: Distribution systems optimization with computational intelligence algorithmsg
Abstract  Full Text

Clara IONESCU, Robin DE KEYSER: On the potential of using fractional-order systems to model the respiratory impedance
Abstract  Full Text

Mihai VLASE, Radu NEGULESCU: Data mining for scientific publications
Abstract  Full Text

Adina COCU: Possibilistic networks for uncertainty knowledge processing in student diagnosis
Abstract  Full Text

Gheorghe PUSCASU, Bogdan CODRES, Alexandru STANCU: Identification of the non-linear systems using internal recurrent neural networks
Abstract  Full Text

Alexandru STANCU, Gheorghe PUSCASU, Bogdan CODRES: Aspects regarding the neuro-adaptive control structure properties.Application to the nonlinear pneumatic servo system benchmark
Abstract  Full Text

Ciprian VLAD, Nicolaos Antonio CUTULULIS, Julie LEFEBVRE, Emil CEANGA: Some results concerning no-storage wind-diesel systems control
Abstract  Full Text

Emil ROSU, Mihai CULEA, Teodor DUMITRIU, Traian MUNTEANU: Indirect control of a single-phase active power filter
Abstract  Full Text

Mihai CULEA, Teodor DUMITRIU, Mihai NICHITA, Traian MUNTEANU: Stationary frame active power filter control based on multiresolution analysis
Abstract  Full Text

Teodor DUMITRIU, Mihai CULEA, Mihai NICHITA, Traian MUNTEANU: Non-conventional method for friction compensation in DC drive position tracking
Abstract  Full Text

Marian GAICEANU: Power conditioning system topology for grid integration of wind and fuell cell energy
Abstract  Full Text

Nicolae BADEA , Ion VONCILA: The influence of non-homogenous dielectric material in the waveguide propagation modes
Abstract  Full Text

 

 

Herbert PEREMANS, Bertrand FONTAINE: Sonar target localization based on spike coded spectrograms


Abstract: Target location is coded into the pattern of spikes that run up the auditory nerve to the bat's brain. Realistic scenes containing multiple, closely spaced, reflectors give rise to complex echo signals consisting of multiple filtered copies of the bat's own vocalisation. Some of this filtering is due to the directivity of the bat’s reception system i.e., the outer ears, and some of it is due to sound absorption and the reflection process. The analysis below concentrates on the conspicuous ridges (notches) these filter operations give rise to in the time-frequency representation of the echo as produced by the bat's inner ear. Assuming multiple threshold detecting neurons for each frequency channel it is shown how the distribution of spike times within the generated spike bursts is linked to the presence and characteristics of these notches. A neural network decoding the spike bursts in terms of target location is described.

Keywords: Auditory system, Neural networks, Robot sensing systems, Sonar signal processing.

 

 

 

Radu DOGARU, Manfred GLESNER, Ronald TETZLAFF: Cellular automata codebooks applied to compact image compression


Abstract: Emergent computation in semi-totalistic cellular automata (CA) is used to generate a set of basis (or codebook). Such codebooks are convenient for simple and circuit efficient compression schemes based on binary vector quantization, applied to the bitplanes of any monochrome or color image. Encryption is also naturally included using these codebooks. Natural images would require less than 0.5 bits per pixel (bpp) while the quality of the reconstructed images is comparable with traditional compression schemes. The proposed scheme is attractive for low power, sensor integrated applications.

Keywords: Cellular automata, emergent computation, image compression, binary vector quantization, nonlinear dynamics.

 

 

 

Daniela TARNICERIU, Valeriu MUNTEANU, Florin BELDIANU: Frequency content oriented modification of quantization matrix in DCT-based compression


Abstract: In order to improve the compression rate for comparable values of error metrics, we propose a method to modify the standard quantization matrix used in JPEG, according to image frequency content. Unlike the method which allows varying levels of image compression and quality, by scaling all the elements in the quantization matrix by the same factor, we propose a way to modify differently the quantization step for low and high frequencies, respectively.

Keywords: Image compression, quantization matrix.

 

 

 

Daniela COLTUC, Thierry FOURNEL, Jean-Marie BECKER, Yann BOUTANT: An ICA based method for texture recognition


Abstract: The method proposed in this paper uses the Independent Component Analysis (ICA) for an application of unsupervised recognition of textures. The analysed texture is modelled by a weighted sum of almost statistically independent random signals that are extracted with FastICA algorithm. Each resulting signal is described by its negentropy, more precisely, by one of the approximations used by FastICA algorithm. The approximated negentropies are sorted into descending order and represented by a curve. The final step of the algorithm is the averaging of a certain number of such curves obtained from different zones of the texture. The resulting mean ”negentropy curve” displays a good discriminating power on the tested textures.

Keywords: Independent Component Analysis, Negentropy, Pattern Recognition, Texture.

 

 

 

Ion BOGDAN: Minimizing the error tracking of mobile terminals by Kalman filtering


Abstract: A method to track mobile terminals in a cellular communication network is presented. It uses the received field strength from the surrounding base stations. A subsequent Kalman filtering is used to minimize the tracking error.

Keywords: Cellular networks, Kalman filtering, position tracking.

 

 

 

Valeriu MUNTEANU, Daniela TARNICERIU: Optimal coding for qualitative sources on noiseless channels


Abstract: In this paper we perform the encoding for sources which are only qualitatively characterized, that is, each message the source delivers possesses a certain quality, expressed as cost, importance or utility. The proposed encoding procedure is an optimal one, because it leads to maximum information per code word and it assures a minimum time for the transmission of the source information.

Keywords: Coding, information theory, transmission channels.

 

 

 

Radu DOGARU, Gabriel Nicolae COSTACHE, Octavian DUMITRU, Inge GAVAT: A novel feature extraction method for isolated word recognition based on Nested Temporal Averaging


Abstract: A novel preprocessing method is proposed. It has a reduced complexity and therefore is aimed to be used in low power, VLSI implemented, speech recognizers. Our algorithm extracts a feature vector made from up to 3 feature vectors, each coming from a particular variable length speech sequence. The sequences are nested one into each other while their length is divided by 2 for each nesting operation. Each feature vector is computed as an average, min and max of all 13-dimensional Mel-cepstral coefficients obtained within a sound sequence. On a sound database with 10 speakers speaking 7 different words the classification performance was found to be close and even better than the one obtained using traditional methods (HMMs).

Keywords: Speech recognition, Pattern classification, Neural Networks, Support Vector Machines.

 

 

 

Viorel NICOLAU, Rustem POPA, Constantin MIHOLCA: Spectral density correction of a signal at frequency variable transformation


Abstract: The goal of this paper is to determine analytical expression for the spectral density function of a signal, affected by a known frequency transformation, which do not modify the process energy. Such transformations of frequency variable can frequently appear on spectral density function of a signal, due to physical events (e.g. Doppler effect) or mathematical considerations (e.g. changing the coordinate system). In this case, all components of the spectral density function are modified. The formulas are valid for every spectral component and can be used in signal processing, for model simulation or implementation of advanced algorithm. A case study is illustrated on wave spectrum correction.

Keywords: spectral density, frequency transformation, finite energy, wave spectrum.

 

 

 

Mihai GAVRILAS, Ovidiu IVANOV: Distribution systems optimization with computational intelligence algorithms


Abstract: A dual particle swarm optimization - immune algorithm solution is presented in this paper to deal with the problem of optimum radial reconfiguration and reactive power compensation in distribution systems. The optimization problem uses as minimization function power losses in the distribution system – lines and transformers – and addresses constraints referring lower and upper voltage limits, nodal reactive power limits, topology supply constraints and the maximum number of capacitor banks. The analysis conducted for a pilot and a complex test system has proven the feasibility of the proposed method.

Keywords: Capacitor placement, distribution systems, immune algorithm, particle swarm optimization, reactive power compensation, reconfiguration of open-loop systems.

 

 

 

Clara IONESCU, Robin DE KEYSER: On the potential of using fractional-order systems to model the respiratory impedance


Abstract: This contribution provides an analysis of the human respiratory system in frequency domain by means of estimating the respiratory impedance. Further on, analysis of several models for human respiratory impedance is done, leading to the conclusion that a fractional model gives a better description of the impedance than the classical theory of integer-order systems. A mathematical analysis follows, starting from the conclusions obtained heuristically. Correlation to the physiological characteristics of the respiratory system is discussed.

Keywords: Modeling, respiratory system, non-parametric modeling, parametric modeling, Laplace operator, fractional derivatives, fractional integrals.

 

 

 

Mihai VLASE, Radu NEGULESCU: Data mining for scientific publications


Abstract: Searching scientific literature on the Web is a difficult task because of the large volume and the complex dynamics of the scientific literature and because of the complexity and narrow target of typical queries. The problem is compounded by differences among publication standards and formats used in various fields of knowledge. In this paper we review several specific solutions that apply or adapt data mining techniques to searching scientific publications.

Keywords: Search engine, relevance, rank, citations.

 

 

 

Adina COCU: Possibilistic networks for uncertainty knowledge processing in student diagnosis


Abstract: In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.

Keywords: Qualitative uncertainty management, intelligent computer based learning system, possibilistic network, student diagnosis, student modeling.

 

 

 

Gheorghe PUSCASU, Bogdan CODRES, Alexandru STANCU: Identification of the non-linear systems using internal recurrent neural networks


Abstract: In the past years utilization of neural networks took a distinct ampleness because of the following properties: distributed representation of information, capacity of generalization in case of uncontained situation in training data set, tolerance to noise, resistance to partial destruction, parallel processing. Another major advantage of neural networks is that they allow us to obtain the model of the investigated system, systems that is not necessarily to be linear. In fact, the true value of neural networks is seen in the case of identification and control of nonlinear systems. In this paper there are presented some identification techniques using neural networks.

Keywords: Identification, recurrent neural networks, training.

 

 

 

Alexandru STANCU, Gheorghe PUSCASU, Bogdan CODRES: Aspects regarding the neuro-adaptive control structure properties.Application to the nonlinear pneumatic servo system benchmark


Abstract: Generally, control techniques based on multilayer neural networks are used especially in the case of non-linear process and less in case of linear process, because classical control techniques are good enough and relatively easy to implement in linear case. In this paper it will be presented a adaptive neural control structure with application to an pneumatic servo system. This system has many advantages, such as high speed, high flexibility and low price. However, applications of this system are restricted because the physical parameters have strong nonlinearity, inaccuracy and uncertainty, so it’s very difficult to find an optimal controller by means of traditional control theory.

Keywords: Neural networks, reference model, neuro-adaptive control.

 

 

 

Ciprian VLAD, Nicolaos Antonio CUTULULIS, Julie LEFEBVRE, Emil CEANGA: Some results concerning no-storage wind-diesel systems control


Abstract: This paper deal with the dynamics of an autonomous no storage wind-diesel system, comprising a diesel generator and a controlled wind system with a hypo/hyper synchronous cascade. The objective is to maximize the wind energy penetration rate, by an optimization control system, respecting the quality standard concerning the frequency deviation in the AC local grid. Also, the influence of the diesel drive train on the system’s dynamics performances is discussed.

Keywords: Wind energy, Wind-diesel system, Wind energy penetration rate, Optimization control system, Frequency deviation.

 

 

 

Emil ROSU, Mihai CULEA, Teodor DUMITRIU, Traian MUNTEANU: Indirect control of a single-phase active power filter


Abstract: The control of shunt active power filters using PWM inverters consists in generating a reference by separating, using different methods, the harmonics to be eliminated. The methods used are time-consuming and need dedicated control and signal processing equipments. To avoid these setbacks a new method is proposed in the paper. The active power filter is a current PWM rectifier with voltage output and with a capacitor on the DC side. The PWM rectifier is controlled so that the sum of its current and the load’s current is a sinusoid. The control block as well as simulation results are presented.

Keywords: Active power filters, PWM rectifiers, hysteresis control, THD.

 

 

 

Mihai CULEA, Teodor DUMITRIU, Mihai NICHITA, Traian MUNTEANU: Stationary frame active power filter control based on multiresolution analysis


Abstract: The paper presents an active power filter control method. The reference signal is generated in the stationary reference frame a-ß using multiresolution analysis and the controllers used are P-resonant controllers, suitable for this particular application due to the fact that the steady-state error is zero for sinusoidal references with the frequency corresponding to the resonant frequency of the controller.

Keywords: Active power filter, multiresolution analysis, resonant controller.

 

 

 

Teodor DUMITRIU, Mihai CULEA, Mihai NICHITA, Traian MUNTEANU: Non-conventional method for friction compensation in DC drive position tracking


Abstract: Friction, especially its nonlinear components, may degrade the tracking performance of any servo drive systems. Focused on high precision positioning of DC electrical drive the paper proposes an easy method to compensate for the friction by using a non-model based compensator developed around a simple control structure. The approach to inhibit the friction influence is based on a compensation signal provided by the mathematical model of the servo positioning DC drive in which the load torque (including friction component) is considered zero. Build on the difference between the command signals of real servo tracking drive and, respectively, of the same servo drive, but no load status, the compensation variable depends only on the usual and measurable states of an electrical drive (current and velocity) The control problem of the servo drive with friction is solved via the gain scheduling of a P controller parameter as function of position reference scale. Good results concerning the tracking errors are achieved for large range of reference test signals, including the micrometer scale.

Keywords: Friction, non-model-based friction compensation, stiction, Stribeck effect, tracking.

 

 

 

Marian GAICEANU: Power conditioning system topology for grid integration of wind and fuell cell energy


Abstract: This paper shows the topology of the hybrid grid-connected power system and the performances of the front-end three-phase power inverter. The renewable sources of the hybrid power system consist of a solid oxide fuel cell and a wind-turbine. This type of combination is the most efficient one. The proposed topology benefits of the one common DC-AC inverter which injects the generated power into the grid. The architecture diminishes the cost of the power conditioning system. Moreover, due to the power balance control of the entire power conditioning system the bulk dc link electrolytic capacitor is replaced with a small plastic film one. The final power conditioning system has the following advantages: independent control of the reactive power, minimize harmonic current distortion offering a nearly unity power factor operation (0,998) operation capability, dc link voltage regulation (up to 5% ripple in the dc-link voltage in any operated conditions), fast disturbance compensation capability, high reliability, and low cost. The experimental test has been performed and the performances of the grid power inverter are shown.

Keywords: Renewable energy, fuel cell, SOFC, wind-turbine, power conditioning, grid-interface.

 

 

 

Nicolae BADEA , Ion VONCILA: The influence of non-homogenous dielectric material in the waveguide propagation modes


Abstract: The aim of this paper is to indicate the equations of electromagnetic wave in homogenous and non-homogenous dielectric material, estabilising the bundary conditions and solves by FEM the equations of the electromagnetic wave in the rectangular cavity. By numeric simulation of the waveguide in the cavity there have been studied the modifications of both the ways of propagation and the field’s distribution. The non-homogenous mediums afectes the field’s amplitude, obtaining a non-homogenous distribution. Poyting vector of the wave’s transmision, indicates the energetic flux’s concentration in the air besides the dielectric material.

Keywords: Electromagnetic surface waves, waveguide, Dielectric waveguides, Rectangular waveguides.