Generalized Gaussian distribution (GGD) includes specials cases when the shape parameter equals p = 1 and p = 2. It corresponds to Laplacian and Gaussian distributions respectively. For p → ∞, f(x) becomes a uniform distribution, and for p → 0, f(x) approaches an impulse function. Chapeau-Blondeau et al. considered another special case p = 0.5. The article discusses more peaky case in which GGD p = 1/3.
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Petitcolas has proposed a steganographic technique called MP3Stego which can hide secret messages in a MP3 audio. This technique is well-known because of its high capacity. However, in rare cases, the normal audio encoding process will be terminated due to the endless loop problem caused by embedding operation. In addition, the statistical undetectability of MP3Stego can be further improved. Inspired by MP3Stego, a new steganographic method for MP3 audio is proposed in this paper. The parity bit of quantization step rather than the parity bit of block size in MP3Stego is employed to embed secret messages. Compared with MP3Stego, the proposed method can avoid the endless loop problem and achieve better imperceptibility and higher security.
The multi-direction digital moving mask method, employing the superposition of the exposure along various moving directions, is developed for fabricating continuous microstructures. The mask pattern corresponding to each moving direction is determined by projecting the target dose profile in the corresponding moving direction. All the mask patterns are dynamically exposed on the same substrate layer by layer so as to form a 3D profile of the exposure dose. The selection criterion of a quantization number and moving-direction number is discussed. For verification of the multi-direction moving method, experiments are performed to fabricate a square pyramid array and square-based microlens array by moving along two orthogonal directions, and round-based microlens array by moving along six directions.
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In a certain sense a perfect fluid is a generalization of a point particle. This leads to the question as to what is the corresponding generalization for extended objects. Here the lagrangian formulation of a perfect fluid is much generalized by replacing the product of the co-moving vector which is a first fundamental form by higher dimensional first fundamental forms; this has as a particular example a fluid which is a classical generalization of a membrane; however there is as yet no indication of any relationship between their quantum theories.
Obliczanie niepewności wyników realizacji algorytmów przetwarzania w systemie pomiarowym wymaga losowego opisu błędu kwantowania. Podstawą uzyskiwania tego rodzaju opisu jest analiza właściwości układu realizującego kwantowanie. W pracy przedstawiono wstępne wyniki badań symulacyjnych wybranych rozwiązań kwantyzatorów przeprowadzonych przy użyciu metody Monte Carlo, co pozwala na uzyskanie histogramów charakteryzujących w pełni losowe właściwości błędu kwantowania.
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Digital processing in measuring systems requires, shown in Fig. 1, digitalization of varying in time continuous signals. Quantization of samples is a measuring process, so it should be described in metrological categories. Complete information about inaccuracy of quantization can be given by probabilistic description of error sources arousing during this operation []. The paper deals with analysis of random properties of quantization errors on example of chosen realizations of quantizers. The analysis has been made by using Monte Carlo method, which permits to obtain, in a relatively simple way, large sets of data that can be presented as histograms. The investigated types of quantizers are shown in Figs. 2, 6 and 8, while the exemplary histograms in Figs. 4, 5, 7 and 9. The histograms can be divided into two categories. The first one describes properties of quantization errors in the situation when the quantized quantity changes randomly in its measuring range. The quantization error in this case has the rectangular or triangle distribution. The second kind of histograms shows properties of errors when the quantized quantity is constant in time. In this case the histograms contains one or two values only so the properties of the errors should be seen as deterministic. Moreover, the shape of histogram depends on the value of the quantized quantity. One may try to average a series of quantization results but the obtained the results vary dependently on the measure value, number of the series elements an kind of the quantize. The general conclusion is that in the second case there is necessary to continue investigations directed to the problems of averaging data obtained from ADC converters.
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We present an effective message embedding scheme for 3D models. We propose the unit length as the quantizer to generate an embedding order list and an embedding index list. Our scheme considers every two elements in the embedding order list as the order pair, and we embed 3 bits of 0 or 1 secret message into the index pair associated with the order pair. The message embedding is effective requiring, at most, adding 1 to, or subtracting 1 from, the index pair. This reflects a slight perturbation of a points coordinates where the magnitude of the perturbation is no greater than one unit length. Our algorithm achieves a high embedding capacity, being 4.5 times the number of points in the point cloud models. This amount of capacity allows us to convey a 502x502 resolution of the black-and-white image into a point cloud model consisting of 56,194 points for covert communication. The capacity magnitude is 50%-75%higher than that of the current state-ofthe-art algorithms, yet the model distortion due to the message embedding is smaller than that of our counterparts. Our algorithm is robust against translation, rotation, and uniformly scaling operations. It is fast, simple to implement, and the message can be extracted without referring to the original point cloud model. We believe our scheme is appropriate for most point cloud models.
Companding, as a variant of audio level compression, can help reduce the dynamic range of an audio signal. In analog (digital) systems, this can increase the signal-to-noise ratio (signal to quantization noise ratio) achieved during transmission. The µ-law algorithm that is primarily used in the digital telecommunication systems of North America and Japan, adapts a companding scheme that can expand small signals and compress large signals especially at the presence of high peak signals. In this paper, we present a novel multi-exponential companding function that can achieve more uniform compression on both large and small signals so that the relative signal strength over the time is preserved. That is, although larger signals may get considerably compressed, unlike µ-law algorithm, it is guaranteed that these signals after companding will definitely not be smaller than expanded signals that were originally small. Performance of the proposed algorithm is compared with µ-law using real audio signal, and results show that the proposed companding algorithm can achieve much smaller quantization errors with a modest increase in computation time.
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A geometric model for the quantum nature of interaction fields is proposed. We utilize a trivial fibre bundle whose typical fibre has a multiconnectivity characterized by a discrete group Γ. By seeing Γ as a gauge group with global action on each fibre, we show that the corresponding field strength is non-zero only on the future part of the light cone whose vertex is at the interaction point. When the interaction is submitted to the symmetries of a Lie group G, we consider the gauge group G x Γ. The field strength of the gauge having this group includes a term expressing the quantization of the interaction field described by G. This geometric interpretation of quantization makes use of topological arguments similar to those applied to explain the Aharonov-Bohm effect. Two examples show how this interpretation applies to the cases of electromagnetic and gravitational fields.
This paper deals with the amplitude estimation in the frequency domain of low-level sine waves, i.e. sine waves spanning a small number of quantization steps of an analog-to-digital converter. This is a quite common condition for high-speed low-resolution converters. A digitized sine wave is transformed into the frequency domain through the discrete Fourier transform. The error in the amplitude estimate is treated as a random variable since the offset and the phase of the sine wave are usually unknown. Therefore, the estimate is characterized by its standard deviation. The proposed model evaluates properly such a standard deviation by treating the quantization with a Fourier series approach. On the other hand, it is shown that the conventional noise model of quantization would lead to a large underestimation of the error standard deviation. The effects of measurement parameters, such as the number of samples and a kind of the time window, are also investigated. Finally, a threshold for the additive noise is provided as the boundary for validity of the two quantization models.
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Przedstawiono twierdzenia Wirdowa i warunki odtwarzalności dla kwantowania w zastosowaniu do momentów sygnału. Dokonano analizy obciążenia estymatora momentu rzędu 2. (wartości średniokwadratowej) oraz momentu łącznego rzędu 2. (funkcji korelacji wzajemnej) spowodowanych niespełnieniem tych warunków. Szczególną uwage poświęcono sygnałom o rozkładach normalnych. Dokonano analizy estymatora wartości średniokwadratowej. Wyprowadzono i przedyskutowano zależność określającą obciążenie funkcji korelacji wzajemnej.
EN
The quantizing theorems of Widrow of quantizing rerconstruction conditions for the estimation of the signal moments are presendet. An analysis of the bias of the second-order moment ( mean square value ) estimator and the joint second-order moment ( crosscorrelation function ) estimator, caused by non-satisfied quantizing reconstruction conditions, is carried out. Special attention is devoted to the normal pdf signals. An analysis of the bias of the mean square value estimator is carried out. Analytic for crosscorrelation function bias is derived and discussed.
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Measurements in a system are performed automatically by using data acquisition cards typically consisting of an amplifier, a samplelhold circuit and an analog-to-digital converter. The results obtained from these cards are processed by a program. The processing algorithms are often of sophisticated numerical structure and, in this situation, the determination of inaccuracy of the system output data needs building a system error model. The base of the error model construction should be a model of a single measurement result delivered at the output of the card. The paper presents a model which has been obtained on the basis of an analysis of the quantization process consisting in a direct comparison of the measured quantity with a standard of quantum character. In a measuring system the quantization is realized by an AD converter, which measures a sample of a time-varying input quantity. The assumption that the sampling is performed at any moment enables obtaining the model described in probabilistic categories, which may be the basis of the uncertainty calculation of the system output data.
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W artykule opisano procedurę obliczania niepewności wyniku pojedynczego pomiaru wykonanego za pomocą przyrządu cyfrowego. Formalizacja tej procedury oparta jest na analizie procesu kwantowania, który stanowi podstawę pomiaru w przyrządzie cyfrowym. Rozważania zilustrowano liczbowo wykorzystując woltomierz z podwójnym całkowaniem jako przykładowy przyrząd cyfrowy. Rozpatrzono wpływ opisanej formalizacji na liczbę miejsc znaczących wyniku pomiaru zapisanego w postaci przedziałowej.
EN
The paper describes a procedure of uncertainty calculation of a single measurement result performed by a digital instrument. Formalization of this procedure is derived from the analysis of a quantization process which is the basis of a digital measuring instrument activity. Considerations are illustrated with an example in which a dual-slope AD converter has been analysed. Influence of the described formalization on the number of significant digits of the single measurement result written in an interval form is discussed.
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Analog-to-digital (A/D) converters are basic elements of measuring chains since they deliver measurement data being a carrier of digital information in measurement instruments and systems. Taking into account that the quality of the information depends on accuracy of data, one should evaluate the uncertainty of A/D conversion results. One of the uncertainty component is connected with the linearity error of an A/D converter. This error has to be contained in the uncertainty budget, however, it is possible if the error is described in probabilistic categories. The paper presents a way of obtaining such a kind of description, the basis of which is an analysis of A/D conversion as a quantization process consisting in a comparison of the measured quantity with a standard composed of quanta. The linearity error is treated as an effect of random distortion of quanta. A general model of a quantization result, containing both the quantization error and the error caused by quantum distortion, as well as the error generated by thermal noise, has been described. An analysis of correlation coeffcients between these errors has been performed using the Monte Carlo method. A procedure of uncertainty calculation on the basis of the known error distribution has been presented.
Kwantyzacja danych wideo występuje w różnych odmianach, niemal w każdym algorytmie kompresji obrazów. Ma ona na celu redukcję mniej istotnych danych, jednocześnie zwiększając stopień kompresji danych, w następującym po kwantyzacji procesie kodowania o zmiennej długości słowa. W niniejszej publikacji opisany zostanie szczegółowo proces skalowania wstępnego i kwantyzacji w standardzie cyfrowego wideo. Przedstawiona zostanie również architektura potokowa wykonująca operację kwantyzacji odwrotnej, zrealizowana jako jednostka przetwarzająca sprzętowego dekodera realizowanego przez układ reprogramowalny.
EN
Video data quantization is present, in different variations, in almost all video compression algorithms. Its purpose is to reduce less important data, while at the same time increase the efficiency of video compression, in the consecutive variable length coding process. In this paper preliminary scaling and quantization algorithms used in digital video standard (DV - Digital Video), will be described in details. Implementation of inverse quantization algorithm in the pipeline architecture, as one of processing elements in complete DV decoder, will be presented.
Działania realizowane przez przetwornik A/C typu Sigma-Delta opisano w artykule jako proces pomiaru podzielony na trzy etapy: przetwarzanie analogowe, kwantowanie i przetwarzanie cyfrowe. Poddano analizie podstawowe źródła błędu, a następnie określono wpływ decymacji i filtracji na właściwości wypadkowego błędu wyniku pomiaru. Rozważania analityczne zilustrowano wynikami symulacji uzyskanymi przy użyciu metody Monte Carlo.
EN
A basic scheme of a Sigma-Delta AD converter, analyzed in the paper, is shown in Fig. 1. The converter performs a quantization process, which can be described as compensation of the charge, delivered to the integrator from the source of the measured voltage Ux, with quanta of charge obtained synchronously with clock CLK when the switch P is closed. Value of a charge quantum is given by Eq. (1) and the balance state of the quantizer by Eq. (2). Basing on this equation one can obtain expression (3) describing a measurement result and Eq. (4) that describes value of a voltage quantum. All stages of the processing made by Sigma-Delta converter, i.e. analog conversion, quantization and digital processing, are shown in Fig. 3. One can distinguish three main error sources in this process - input error described by Eq. (6) and two errors connected with quantization: quantization error and standard error caused by dispersion of the quanta values (Eqs. (8), (9) and Fig. 3). Next considerations deal with analysis of decimation and averaging influence on the quantization error and the standard error. Fig. 4 shows exemplary histogram of the quantization error after averaging and Fig. 5 the error being the result of composition of both mentioned errors. Having the errors described one can calculate uncertainty of a measurement result using the procedure presented in paper [3].
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We show that the Hopf algebra on a transformation groupoid F = E x G where G is a finite group acting on the total space of a principal fibre boundle over M = E/G, is the cross product of the algebras C°°(E) and CG. We study duality properties of this algebra, and consider quantization on orbit spaces program in this context.
Celem artykułu jest analiza wpływu różnych rodzajów kwantowania na dokładność wyznaczania funkcji korelacji wzajemnej sygnałów. Rozważono dwa sposoby kwantowania: kwantowanie deterministyczne oraz randomizowane. Dokonano porównania wyników otrzymanych w obu przypadkach. Badania symulacyjne przeprowadzono z zastosowaniem programu ImeCorr opracowanego w środowisku LabWindows. Badano dokładność estymatorów funkcji korelacji wzajemnej otrzymanych z użyciem przetwornika 3-, 8- i 12-bitowego dla argumentu równego zero.
EN
The influence of quantization on the cross-correlation function determination of signals is discussed. The relations for cross-correlation function and its digital estimators are given. A method for evaluating the estimator accuracy is presented. Different types of quantization are considered. The formulas describing the quantization ways and related illustrations are presented. In Figures 1, 2 and 3 deterministic, randomized and pseudo-randomized quantization are shown, respectively. To obtain the simulation results, the program ImeCorr prepared in LabWindows was applied. The 3-, 8- and 12-bits quantizers were taken into account. The research results were compared. In Table 1 the values of the relative bias and the relative standard error are shown. It was observed that for 3-bits quantizers the bias had similar values. For the 8- and 12-bits converters the bias is smaller for the randomized and pseudo-randomized quantizing than for the deterministic one. The randomized and pseudo-randomized quantization is a source of the larger standard error than the deterministic quantization. The standard error is smaller for the pseudo-randomized quantization than for the randomized one.
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In this paper, we consider the design of interconnected $H_∞$ feedback control systems with quantized signals. We assume that a decentralized dynamic output feedback has been designed for an interconnected continuous-time LTI system so that the closed-loop system is stable and a desired $H_∞$ disturbance attenuation level is achieved, and that the subsystem measurement outputs are quantized before they are passed to the local controllers. We propose a local-output-dependent strategy for updating the parameters of the quantizers, so that the overall closed-loop system is asymptotically stable and achieves the same $H_∞$ disturbance attenuation level. Both the pre-designed controllers and the parameters of the quantizers are constructed in a decentralized manner, depending on local measurement outputs.
Opisano wyniki badania przewodności elektrycznej i cieplnej nanostruktur – obiektów o rozmiarach atomowych. Badano kwantowanie przewodności obu rodzajów. W wielu eksperymentach przeprowadzonych w Politechnice Poznańskiej z nanodrutami meta- licznymi potwierdzono zjawisko kwantowania przewodności elektrycznej.
EN
In the paper one described investigations on electrical and thermal conductance of nanostructures - the objects with atomic sized. In particular the quantization of both electrical and thermal conductance was investigated. In many experiments in Poznan University of Technology quantization of electrical conductance was confirmed.
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