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1

Modelling and Measurement of Folk Guitar : Truss Rod and Strings in Numerical Analysis of Tone

Bielski Paweł Michał, Kujawa Marcin, Lubowiecka Izabela

Archives of Acoustics

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2019

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Vol. 44, No. 1

35--49

EN

The study makes an attempt to model a complete vibrating guitar including its non-linear features, specifically the tension-compression of truss rod and tension of strings. The purpose of such a model is to examine the influence of design parameters on tone. Most experimental studies are flawed by uncertainties introduced by materials and assembly of an instrument. Since numerical modelling of instruments allows for deterministic control over design parameters, a detailed numerical model of folk guitar was analysed and an experimental study was performed in order to simulate the excitation and measurement of gitar vibration. The virtual guitar was set up like a real guitar in a series of geometrically non-linear analyses. Balancing of strings and truss rod tension resulted in a realistic initial state of deformation, which affected the subsequent spectral analyses carried out after dynamic simulations. Design parameters of the gitar were freely manipulated without introducing unwanted uncertainties typical for experimental studies. The study highlights the importance of acoustic medium in numerical models.

2

Modelowanie kartograficzne z wykorzystaniem neurorozmytych automatów komórkowych

Olszewski R.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2003

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Vol. 13a

171--180

PL

Mapa jako środek przekazu informacji chorologicznej, tj. informacji o rozmieszczeniu obiektów i zjawisk w przestrzeni geograficznej, podlega ograniczeniom wynikającym z zakresu pojemności informacyjnej. W procesie przekazu kartograficznego istnieje zatem konieczność celowego uogólnienia informacji źródłowej realizowanego poprzez generali-zację. Jednym ze sposobów generalizacji jest agregacja danych przestrzennych. Istnieje wiele algorytmicznych metod agregacji, większość z nich związana jest z generalizacją danych zapisanych w formacie wektorowym. Dla danych źródłowych w postaci rastrowej wymaga to pracochłonnej wstępnej konwersji formatu raster → wektor oraz wynikowej konwersji wektor → raster. Autor podjął próbę zastosowania bezpośredniej agregacji obiektów powierzchniowych na obrazach rastrowych. Przeprowadzone badania wskazują na celowość zastosowania metod tzw. sztucznej inteligencji obliczeniowej, jako metody kartograficznego modelowania tak zdefiniowanych danych źródłowych. W artykule omówiono trzy wybrane metody sztucznej inteligencji obliczeniowej (automaty komórkowe, sztuczne sieci neuronowe i systemy wnioskowania rozmytego) oraz ich zastosowanie w procesie generalizacji kartograficznej.

EN

Investigations which have been performed by the author justify utilisation of methods of the, so-called, artificial intelligence, as a complex method of cartographic modelling of source data. Of the many existing methods for area aggregation a majority concern maps in vector format. The author investigated some approaches to direct aggregation of area objects in raster maps. This includes cellular automata, neural networks and fuzzy inference systems. The essence of cellular automata is the ability to create complex, global patterns and spatial behaviour, based on simple rules of changes of local range and on knowledge concerning individual cells. Therefore a model of the cartographic generalization process, combining the nature of quantitative generalization of the content and the form with the nature of qualitative generalization, may be developed based on the theory of non-linear cellular automata.

3

Non-linear time series modelling in financial economics

Chappell D.

Management

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2000

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Vol. 4, no 1

85-100

EN

In this paper we give a summary of some of the non-linear time series modeIs. We present and discuss the properties of the random walk model, ARCH (auto-regressive conditional heteroscedasticity) and GARCH (generalised ARCH) classes of models, threshold auto-regressive models, smooth transition autoregressive models, bilinear models and others. We give examples of modelling chosen economic and financial phenomena and we offer modelling strategy based on flow chart.

4

Dynamic Neural Networks for Process Modelling in Fault Detection and Isolation Systems

Korbicz J., Patan K., Obuchowicz A.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

519-546

EN

A fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points.To improve the quality of neural modelling, two optimization problems are included in the construction of such dynamic networks: searching for an optimal network architecture and the network training algorithm. To find a good solution, the effective well-known cascade-correlation algorithm is adapted here. The residuals generated by a bank of neural models are then evaluated by means of pattern classification. To illustrate the effectiveness of our approach, two applications are presented: a neural model of Narendra's system and a fault detection and identification system for the two-tank process.

5

Nonregular nonlinear sector modelling

Piegat A.

Applied Mathematics and Computer Science

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1998

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Vol. 8, no 3

611-632

EN

Fuzzy modeIs realize human-like modelling schemes. However, a human being can create in his mind relatively simple modeIs of real systems with maximum two inputs. The reason is that human models are based on rectangular lattice partitions of the input spaces. Such a partition enables us to understand the modelled system, which is a great advantage of fuzzy modelling. Despite this, the rectangular lattice partition makes modelling of systems with large numbers of inputs and those realizing complicated inputs/output mappings impossible or very difficult. The paper puts forward a self-organizing and self-tuning method for modelling nonlinear systems. It is based on a nonrectangular partition of the input space. The conclusions of rules can be here linear or nonlinear. For the latter, a special delinearization function (SDL) is proposed. It makes it possible to decrease considerably the number of rules, which results in efficient modelling. Also, the amount of measurement information from the system needed to learn a model can be decreased considerably.