Topic
Sine wave
About: Sine wave is a research topic. Over the lifetime, 12183 publications have been published within this topic receiving 93013 citations. The topic is also known as: sinusoid.
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TL;DR: Results have been presented for the far field intensity distribution in the diffraction images and the general triangular wave response of the system.
Abstract: Imagery of a general periodic triangular wave object formed by an aberration-free narrow rectangular aperture (slit) with tapered illumination, has been investigated. The system is assumed to be operating in incoherent light. Results have been presented for the far field intensity distribution in the diffraction images and the general triangular wave response of the system. An object function which gives a wave response nearly similar to that of sine wave has been pointed out.
21 citations
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13 Jul 2011
TL;DR: In this article, a sine wave inverter parallel system with variable current ratio is presented, which is characterized by comprising a monitoring management unit and one or a plurality of inverter power supply modules in redundancy parallel operation.
Abstract: The invention discloses a sine wave inverter parallel system with variable current ratio, which is characterized by comprising a monitoring management unit and one or a plurality of inverter power supply modules in redundancy parallel operation; the monitoring management unit is connected with all the inverter power supply modules through a communication signal wire; the inverter power supply modules are mutually connected by the communication signal wires, synchronous signal wires and average current signal wires; and each inverter power supply module is simultaneously connected with a DC (Direct Current) input end and an AC (Alternating Current) output end. The proportion of the load current shared by each module of the parallel system provided by the invention can be set as required so as to meet the requirements on uniform load current sharing (current equalization) by parallel inverter power supply modules with same capacity or load current sharing by the inverter power supply modules with different capacities in the parallel system according to different proportions, so that the parallel function of the inverter power supply modules with different capacities is realized.
21 citations
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01 Nov 2013
TL;DR: The design of a high precision device using a Linear Delta manipulator was proposed to compensate for the tremor signal in three translational directions to avoid the friction effect of the small ball joint.
Abstract: In this paper, the design of a high precision device using a Linear Delta manipulator was proposed to compensate for the tremor signal in three translational directions. A Linear Delta manipulator is a suitable tremor suppression device due to the simple structure and high stiffness with the vertical direction in the application of micro manipulation such as microsurgery and cell manipulation. In order to implement the mechanism of the Linear Delta manipulator to the device, three voice coil motors and three linear encoders with high resolution were used. The flexure mechanism was applied to the device to avoid the friction effect of the small ball joint. Finally, the experiments for the validation of the proposed device were performed as follows: (1) position control in each axis for accuracy, and (2) sine wave tracking (500 μm, 12Hz) for bandwidth of the system.
21 citations
01 Jan 2000
TL;DR: In this article, the authors review the general properties of the wavelet transform, both in its continuous and its discrete versions, in one or two dimensions, and describe some of its applications in signal and image processing.
Abstract: We review the general properties of the wavelet transform, both in its continuous and its discrete versions, in one or two dimensions, and we describe some of its applications in signal and image processing. We also consider its extension to higher dimensions and to the space-time context, for the analysis of moving objects. 1. MOTIVATION: WHAT IS WAVELET ANALYSIS? Wavelet analysis is a particular timeor space-scale representation of signals which has found a wide range of applications in physics, signal processing and applied mathematics in the last few years. In order to get a feeling for it and to understand its success, let us consider first the case of one-dimensional signals. It is a fact that most real life signals are nonstationary. They often contain transient components, sometimes very significant physically, and mostly cover a wide range of frequencies. In addition, there is frequently a direct correlation between the characteristic frequency of a given segment of the signal and the time duration of that segment. Low frequency pieces tend to last a long interval, whereas high frequencies occur in general for a short moment only. Human speech signals are typical in this respect. Vowels have a relatively low mean frequency and last quite long, whereas consonants contain a wide spectrum, up to very high frequencies, especially in the attack, but they are very short. Clearly standard Fourier analysis is inadequate for treating such signals, since it looses all information about the time localization of a given frequency component. In addition, it is very uneconomical. If a segment of the signal is almost flat, i.e., uninteresting, one still has to sum an infinite series for reproducing it. Worse yet, Fourier analysis is highly unstable with respect to perturbation, because of its global character. For instance, if one adds an extra term, with a very small amplitude, to a linear superposition of sine waves, the signal will barely be modified, but the Fourier spectrum will be completely perturbed. This does not happen if the signal is represented in terms of localized components. Therefore, signal analysts turn to time-frequency (TF) representations. The idea is that one needs two parameters. One, called a, characterizes the frequency, the other one, b, indicates the position in the signal. This concept of a TF representation is in fact quite old and familiar. The most obvious example is simply a musical score! If one requires, in addition, the transform to be linear, a general TF transform will take the form: s(x) 7→ S(b, a) = ∫ ∞ −∞ ψba(x) s(x) dx, (1.1) where s is the signal and ψba the analyzing function (we denote the time variable by x, in view of the extension to higher dimensions). Within this class, two TF transforms stand out as particularly simple and efficient, the windowed or short time Fourier transform (STFT) and the wavelet transform (WT). For both of them, the analyzing function ψba is obtained by a group action on a basic (or mother) function ψ, only the group differs. The essential difference between the two is in the way the frequency parameter
21 citations
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03 Mar 1971TL;DR: In this paper, a serially connected sine wave generator and a pulse shaper were used to reproduce electrophysiological signals in the form of speech-like sound signals.
Abstract: A device for the audible reproduction of electrophysiological signals, which includes a serially connected sine wave generator and pulse shaper in which these signals are reproduced in the form of speech-like sound signals, and a pair of band pass filters of which one is frequency tunable to vary the monotonic signals from the pulse shaper in response to deviations in the electrophysiological signals so that the deviations are reproduced as speech-like deviations in these sound signals.
21 citations