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This paper is devoted to the developing of speech character vector based on the arithmetic Fourier transform for speech recognition tasks. The calculation complexity and accuracy of three spectrum methods- fast Fourier transform (FFT), linear prediction (LP) method and arithmetic Fourier transform (AFT) were estimated. It was found that AFT is very useful to calculate speech mel-parameters and provides...
Impedance control is the most favorite control of robot manipulators in contact with environment. The dynamic behavior of robotic system in response to environment is prescribed by an impedance model. This model is certain and linear while the robot manipulator is uncertain and nonlinear. So the major challenge is overcoming uncertainty and nonlinearity to dominate the desired impedance model. This...
In a recent paper Mulgrew [1] proposed a nonlinear filtering structure which utilises a set of orthonormal expansions to model nonlinear dynamical systems. Provisional results were presented for a simple 1-dimensional system. In this paper we extend the analysis of this structure to multi-dimensional filtering, and examine the application of the orthonormal structure for nonlinear system identification...
A novel approach is proposed for overcoming the multiple minima problem, present in the learning of a supervised neural network. It allows to connect rational function approximations to neural networks and is based on the use of a truncated Fourier expansion for determining: 1) the architecture; 2) the parameters of the net, avoiding local minima in an efficient way.
A novel approach is proposed for overcoming the multiple minima problem, present in the learning of a supervised neural network. It allows to connect rational function approximations to neural networks and is based on the use of a truncated Fourier expansion for determining: 1) the architecture; 2) the parameters of the net, avoiding local minima in an efficient way.
This paper considers the problem of non uniform sampling in the case of finite energy functions and random processes, not necessarily approaching to zero as time goes to infinity. The proposed method allows to perform exact signal reconstruction, spectral estimation or linear filtering directly from the non-uniform samples. The method can be applied to either lowpass, or bandpass signals.
In this paper, we present an algebraic description of the aliasing phenomena evident in the linear sampling process of multidimensional periodic band limited signals. Opposed to the classical Shannon sampling, periodic band limited signals underlie a different aliasing structure providing further freedom in the sampling strategy due to the discreteness of the spectrum. An algebraic formulation of...
We propose a new approach to modelling almost periodic signals and to model-based estimation of such signals from noisy observations. The signal model is based on Fourier series where both the coefficients and the fundamental frequency can continuously change over time. This signal model can be represented by a factor graph which we use to derive message passing algorithms to estimate the time-dependent...
This paper presents a robust seal imprint verification method with rotation invariance. The rotation invariant feature is represented by the absolute value of Fourier coefficients of log-polar image of seal imprint on circles with different radii. Firstly, the feature vector of a seal imprint is defined by the above absolute value of Fourier coefficients of the log-polar image. Secondly, the feature...
This paper analyses periodic gaits of multi-legged locomotion systems. The joint signals are studied in the Fourier domain, namely from the point of view of its reproducibility through low-pass actuators. The influence of several parameters is also considered and their critical values are investigated.
This work develops an adaptive High Power Amplifier (HPA) predistorter that applies the fuzzy logic and fuzzy set theory. As Volterra and Fourier series models or Neural Networks, a fuzzy logic system (FLS) is a nonlinear function approximated and we demonstrate its ability to compensate the nonlinear distortions for orthogonal multicarrier transmitters and relay stations. When compared with Volterra...
This paper proposes a formation control method of multiple mobile robots based on the modal decomposition by Discrete Fourier Series expansion (DFS). The proposed method controls the formation by controlling the linear velocity and rotational velocity in modal space. The motion of formation is derived by the modal decomposition. Thus, the proposed method obtains the physical meaning of the motion...
We present a generalization of Benford's law for the first significant digit. This generalization is based on keeping two terms of the Fourier expansion of the probability density function of the data in the modular logarithmic domain. We prove that images in the Discrete Cosine Transform domain closely follow this generalization. We use this property to propose an application in image forensics,...
The French mathematician J. B. J. Fourier showed that arbitrary periodic functions could be represented by an infinite series of sinusoids of harmonically related frequencies. This chapter first defines periodic functions and orthogonal functions. A periodic function can be expanded in a Fourier series. The Fourier series of a periodic function is the sum of sinusoidal components of different frequencies...
The French mathematician J. B. J. Fourier showed that arbitrary periodic functions could be represented by an infinite series of sinusoids of harmonically related frequencies. This chapter first defines periodic functions and orthogonal functions. A periodic function can be expanded in a Fourier series. The Fourier series of a periodic function is the sum of sinusoidal components of different frequencies...
Wrinkles exist extensively in space membrane structures, which is one of the main factors affecting the performance of structures. In order to improve the electrical and mechanical properties of space membrane structure. It is important to predict the details of wrinkles, and to design a reasonable controller to reduce the wrinkles. This paper presents a numerical analysis method to predict the amplitude...
How to learn a function from observations of inputs and noisy outputs is a fundamental problem in machine learning. Often, an approximation of the desired function is found by minimizing a risk functional over some function space. The space of candidate functions should contain good approximations of the true function, but it should also be such that the minimization of the risk functional is computationally...
Antenna designed for ultra wide band (UWB) applications should offer a wider bandwidth with minimum distortion of pulses. One such antenna which meets these requirements is the Vivaldi antenna. In a conventional Vivaldi antenna the radiating flare is restricted to take an exponential profile. This paper presents the design of slot loaded Vivaldi antenna, using Fourier series approach. Here the geometry...
The cylindrical wave - planar interface electromagnetic interaction is studied in the current work. To the best of our knowledge, the modeling of this interaction is either computationally intensive, time consuming or of reduced accuracy especially when the source of the cylindrical wave is electrically close to the planar interface. Here we propose a method that alleviates both of those problems...
In this paper, a new Empirical propagation model is presented that is based on the Log-distance model, however with a variable path loss coefficient. It was found that the path loss coefficient depends on the transmitter location within the room due to its impact on wall reflections, where for closer distances of the transmitter within 10λ from the nearest wall it can be modeled by a Fourier Series...
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