TeleMobile Electronics Ltd.

Gdynia, Poland

TeleMobile Electronics Ltd.

Gdynia, Poland

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Michalski J.J.,TeleMobile Electronics Ltd. | Kowalczyk P.,Technical University of Gdansk
IEEE Transactions on Microwave Theory and Techniques | Year: 2011

This paper presents a novel method that is very efficient in solving multidimensional real and complex eigenvalue problems, commonly employed in electromagnetic analysis, which can be transformed into a nonlinear equation. The concept is realized as root tracing process of a real or complex function of N variables in the constrained space. We assume that the roots of the continuous function of N variables lie on the continuous (N-1)-dimensional hyperplane. The method uses regular N and (N-1)-Simplexes, at which vertices the considered function changes its sign. Based on (N-1)-Simplex, the function is evaluated at two new points that are vertices of new regular N-Simplexes for which (N-1)-Simplex is one of its (N-1)-faces. The algorithm, with the usage of stack, runs in an iterative mode tracing the roots inside the volume of the considered simplexes. As a result, the algorithm creates a chain of simplexes in the constrained region. The proposed algorithm is optimal in the sense of the number of function evaluations. The numerical results, real and complex dispersion characteristics of chosen microwave guides, have proven the versatility and efficiency of the proposed algorithm. © 2011 IEEE.


Michalski J.J.,TeleMobile Electronics Ltd
Progress in Electromagnetics Research | Year: 2011

This paper presents a new method of sequential microwave filter tuning. For filters with R tuning elements (including cavities, couplings and cross-couplings), based on physically measured scattering characteristics in the frequency domain, the Artificial Neural Network (ANN) is used to build inverse models of R sub-filters. Each sub-filter is associated to one tuning element. The sub-filters are obtained by successive opening or shorting of resonators and by removing coupling screws. For each sub-filter, the ANN training vectors are defined as physical reflection characteristics (input vectors) and the corresponding positions of the tuning element, which is detuned, in both directions, from its proper setting (output vectors). In the tuning process, such inverse models are used for calculating the tuning element increments needed for setting the tuning element in the proper position. The tuning experiment, conducted on 8- and 11-cavity filters, has shown the performance of the presented method.


Kacmajor T.,TeleMobile Electronics Ltd. | Michalski J.J.,TeleMobile Electronics Ltd.
IEEE MTT-S International Microwave Symposium Digest | Year: 2011

This paper describes a method of microwave filter tuning. The main goal of this research is to take advantage of fuzzy logic and build effective, adaptive approximator - a neuro-fuzzy system. The system was trained with use of samples that contain information about scattering characteristics and corresponding tuning screw deviations. Experiments were performed on four different filters which have 6 to 11 cavities. The results have been then compared with previous works which use artificial neural networks. The system learning phase has been proved to reach lower generalization and learning error. © 2011 IEEE.


Michalski J.J.,TeleMobile Electronics Ltd.
4th Microwave and Radar Week, MRW-2010 - 18th International Conference on Microwaves, Radar and Wireless Communications, MIKON 2010 - Conference Proceedings | Year: 2010

This paper shows how to improve the efficiency of the Artificial Neural Network (ANN) method for the cavity filter tuning. It was proved that the usage of many golden filters in the process of collecting the learning vectors, used in ANN training, has the significant influence in decreasing the ANN generalization error. Thus, the algorithm efficiency is increasing. The generalization error value of ANN, trained on samples from two different filters, as a norm of the filters similarity is proposed. The tuning experiment for the 6-cavities RX filters of GSM diplexer has been demonstrated. In the experiment the ANNs were trained based on the vectors collected from up to five different filters, showing the significant influence of the number of "known filters" on the ANN generalization error.


Gulgowski J.,TeleMobile Electronics Ltd | Michalski J.J.,TeleMobile Electronics Ltd
Progress in Electromagnetics Research | Year: 2012

The idea behind the coupling matrix identification is to find the coupling matrix corresponding to the measured or designed scattering characteristics of the microwave filter. The typical attitude towards coupling matrix parameter extraction is to use some optimization methods to minimize the appropriate cost function. In this paper, we concentrate on the analytic solutions - how they may be found and their application in further optimization processes. In general case, the suggested method generates complex-valued coupling matrix. For a special case of the filter without cross-couplings we give fast and simple recursive method of finding such complex-valued coupling matrix. The method is based on Laplace's formula for expanding the determinant. The complex-valued coupling matrix is used as a good starting point for the optimization methods to find the regular coupling matrix. The examples are presented showing that the optimization arrives to global minimum starting from real parts of complex-valued entries considerably more often than when the starting point is selected randomly.


Michalski J.J.,TeleMobile Electronics Ltd. | Gulgowski J.,TeleMobile Electronics Ltd. | Kacmajor T.,TeleMobile Electronics Ltd. | Piatek M.,TeleMobile Electronics Ltd.
Progress in Electromagnetics Research Symposium | Year: 2012

This paper proposes and investigates a new cost function used in coupling matrix synthesis. In this method filter scattering characteristics are transformed with the use of Daubechies D4 transform, and then compressed. The cost function is defined as Euclidean distance between compressed D4 template reflection and transmission characteristics and the compressed D4 characteristics resulting from the optimized coupling matrix. The important feature of this method is that there is no need to represent filter characteristics in an analytical form (e.g., with the use of total least squares method). The optimization experiments show the performance of the proposed cost function in comparison to the ones already known.


Kacmajor T.,TeleMobile Electronics Ltd | Michalski J.J.,TeleMobile Electronics Ltd
Progress in Electromagnetics Research | Year: 2013

This paper proposes a microwave filter post-production tuning based on an optimization process which finds the vector of deviations of tuning elements that should be applied to tune the filter. To build the system, the coarse set of scattering parameters is collected in such a way that every tuning element is detuned while other elements remain in their proper positions. In the concept, it is assumed that the relation between the positions of tuning elements and filter scattering characteristics can be modelled by the sum of one argument polynomial functions. Each polynomial function depends on the value of only one tuning element. Therefore, the measured filter characteristics can be linearly decomposed to characteristics from the collected coarse set and corresponding tuning element deviations can be found. This is done by way of optimization process. The presented numerical and physical experiments on the 7th order cross-coupled, bandpass filter have verified our approach.


Michalski J.J.,TeleMobile Electronics Ltd
Progress In Electromagnetics Research M | Year: 2010

This paper presents a novel method of cavity filter tuning with the usage of an artificial neural network (ANN). The proposed method does not require information on the filter topology, and the filter is treated as a black box. In order to illustrate the concept, a feed-forward, multi-layer, non-linear artificial neural network with back propagation is applied. The method for preparing, learning and testing vectors consisting of sampled detuned scattering characteristics and corresponding tuning screw deviations is proposed. To collect the training vectors, the machine, an intelligent automatic filter tuning tool integrated with a vector network analyzer, has been built. The ANN was trained on the basis of samples obtained from a properly tuned filter. It has been proved that the usage of multidimensional approximation ability of an ANN makes it possible to map the characteristic of a detuned filter reflection in individual screw errors. Finally, after the ANN learning process, the tuning experiment on 6 and 11-cavity filters has been preformed, proving a very high efficiency of the presented method.


Kacmajor T.,TeleMobile Electronics Ltd. | Michalski J.J.,TeleMobile Electronics Ltd.
2012 19th International Conference on Microwaves, Radar and Wireless Communications, MIKON 2012 | Year: 2012

This paper proposes a new approach In building a multidimensional approximator which maps filter scattering characteristic to the vector containing deviations of tuning element positions. In the concept, it is assumed that relation between positions of tuning elements and filter scattering characteristic can be modeled by the sum of polynomial functions. Each polynomial function only depends on the value of one tuning element. A coarse set of filter characteristics and tuning element positions is used in building the approximator which models this relation. This set is collected by detuning only one tuning element from its proper position at a time, while other elements remain in their proper positions. The presented numerical and physical experiments verified our approach. © 2012 IEEE.


Michalski J.J.,TeleMobile Electronics Ltd. | Kacmajor T.,TeleMobile Electronics Ltd.
2012 19th International Conference on Microwaves, Radar and Wireless Communications, MIKON 2012 | Year: 2012

This elaboration shows that application of Gray generalised codes for determining the position of tuning elements in the process of collecting learning vectors from the filter with the use of a one-arm robot is an alternative for random detuning in the process of customizing the algorithm for microwave filter tuning. Numerical simulations which were performed prove that the method presented here is optimal, considering the minimum number of changes in the arm of the robot (SCARA - one-arm robot) and total angular changes of tuning elements. © 2012 IEEE.

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