The simulation to optimize design is done using **time** **domain** **analysis** tools from CST Microwave Studio which provides wide range oftime **domain** signal that are used in UWB system. The numerical **analysis** ofthe sof tware tools are based on Finite Diﬀerence **Time** **domain** (FDTD) [4]. For comparison purpose, HFSS in frequency **domain** where the numerical **analysis** is based on Finite Element Method (FEM) [5] is performed. The input signal of Gaussian pulse as shown in Figure 2 is used for simulation in CST Microwave Studio because Gaussian signal oﬀers a good mix between **time** and frequency **domain** compactness.

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A large survey on faults in induction motor is carried out by Electric Power Research Institute (EPRI) in 1985.According to this survey found that bearing (41%), stator (37%), rotor (10%) and other (12%) faults occurred in the induction motor. **Time** **domain** refers to a display or an **analysis** of the vibration data as a function of **time**. The **analysis** can be done by visually looking at portions of the **time** **domain** waveform or by examining some statistical parameters related to **time** **domain** **analysis**. In the1980’s, Mathew and Alfredson presented a review of vibration monitoring techniques in the **time** and frequency domains for rolling element bearings. Analysing the vibration signals directly in the **time** **domain** is one of the simplest and Non-intrusive detection techniques.Tandon and Nakra (1993) reported visual inspection of the **time** history of the vibration signals, **time** wave form indices, probability density function, and probability density moments that are easily analyzed using the **time** **domain** **analysis**. Various **time** **domain** statistical parameters have been used as trend parameters to detect the presence of incipient bearing damage. The most commonly used ones are peak, RMS, crest factor and kurtosis. Dyer and Stewart (1978) first proposed the use of kurtosis for bearing fault detection. These values for a damaged bearing tend to be greater than the values for a normal bearing.

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In civil engineering applications, solid materials, such as rubber, are one of the most widely used materials for dampers and base isolations. In this regards, most of the linear analyses in the literature modeled the damping of these materials in the form of viscous damping. However this is not strictly an accurate representation due to the fact that these types of solid materials exhibit a hysteresis in their force-displacement behavior. It has also been shown experimentally that the energy dissipated by a solid material is frequency-independent [1]. On the other hand, energy dissipated by viscous damping is linearly proportional to the excitation frequency. To represent more realistic physical behavior, a complex stiffness model can be used. However, the **time** **domain** **analysis** of this type of damping is challenging due to its non-causality.

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The scope of this paper is the **time**-**domain** **analysis** of an overhead arrangement considering the frequency-dependent behavior of the stratiﬁed earth in the framework of the quasi-TEM approximation. The Nakagawa model for the earth return impedance solution and the FDTD method are used to characterize the transient behavior on overhead lines. The use of the FDTD method requires that all parameters must be in the **time**-**domain** including the earth return impedance. The vector ﬁtting algorithm proposed by Gustavsen and Semlyen in [12] is employed to transform those parameters into **time** **domain**. This transformation deals with a convolution integral of impedance solution and **time** derivatives of currents. Moreover, in the FDTD method, the spatial resolution Δ z and **time** step Δ t must be chosen according to the following stability condition [13] (the Courant-Friedrich-Levy (CFL) condition):

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width of the pulse in **time** **domain**. The frequency information can be extracted by applying the discrete Fourier transformation (DFT) during **time**-marching in the FDTD simulation. The phenomena in the far-field region are frequently of interest as well as in the near-field region. When a **time**-**domain** pulse is used for spectral **analysis**, the far-field information must be extracted from the near-field before sampling for the the DFT. The near-field to far-field transformation may then be applied (see Sec. 2.4.3). In the far- field region, a set of sinc functions appear as the Fourier components corresponding to the diffraction orders. When the structure has an infinite periodicity, a sum of the Fourier components yields discrete signals in the far-field region rather than a continuous pattern. The far-field signals, often called Floquet modes, are governed by the diffraction equation:

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In this subsection, the simulation results are presented to further demonstration of the reliability of the above approach. Three different fractional order systems represented by damped harmonic oscillator equation have been considered to confirm the given analytical results. First, let us use Equations (29)-(31) for ν = 0.25, 0.5 and 0.75 for examinations of influences of the fractional order on the response damping within the period of forced fractional oscillator. Moreover, this gives also possibilities to examine the responses of the oscillator on different form of variations in **time** of the periodic forcing term.

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A new efficient 3D finite difference **time** formulation based on **time** shift operator is used to simulate electromagnetic wave interaction with dispersive chiral medium. The resulting update equations depend only on electric and magnetic field components. There are no additional intermediate vector components, temporal convolution or transformations. The present technique shows a good improvement in memory requirements while keeping on the accuracy and the computational **time** compared with other similar methods.

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In order to consider dynamic soil–structure interaction and non-linear behavior of the structure in dynamic response analyses, it is necessary to calculate the ground resisting force accounting for the frequency dependent of ground impedance. In this paper, a **time**-**domain** difference calculation approach of resisting force is proposed by combining lumped-parameter model and **time**-**domain** recursive model, which can take into account the singular and regular component of foundation impedance completely. Results from numerical example demonstrate that the proposed procedure can represent the property of foundation impedance vary with frequency.

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Abstract: **Time** series **analysis** has been created by four types of experts namely Engineers and Physical Scientists; Economists; Applied Statisticians and Econometricians; and Mathematical Statisticians and Probability. The richness of the subject springs from this diversity of its origins. The history of **time** series **analysis** was not as smooth as one might think. **Time** series **analysis** was divided into two approaches namely Frequency **Domain** and **Time** **Domain** approaches. For Engineers and Physical Scientists, it is natural to regard a **time** series as made up of oscillations at different frequencies. This gives frequency **domain** **analysis**. For Statisticians and Applied research workers in other fields, it is natural to treat the data from the standpoint of correlation and regression relations between successive observations. This gives **time** **domain** **analysis**. There is duality between the frequency **domain** and **time** **domain** approaches to the **time** series **analysis**.

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The purpose of this paper was to introduce and validate a novel method of phase-plane controller stability **analysis** using a unique method called the **Time** **Domain** **Analysis** of Phase- plane Stability (TDAPPS). The intent for the initial development of this method was to create a stability **analysis** tool that could be simple to use and understand, while still providing the information required to quantify a controller’s stability margins. A brief history of phase-plane control in industry was provided along with a high-level description of how a phase-plane controller works. This was followed by a detailed description of the TDAPPS algorithm, including the math and logic involved in its development. Next, the TDAPPS method was compared to the current, most commonly used method for this **analysis**, known as the Describing Function Method. Here, it was determined that both approaches had distinct advantages and disadvantages and that the TDAPPS method was worthy of further development. After describing the simulation environment, a set of basic and, subsequently, more advanced tests were conducted to obtain initial TDAPPS results. The resulting phase and gain margins were tested in the same simulation environment and their merit was discussed along with several ways that the tool could be improved.

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In this paper, we investigate the unique solvability and stability of the **time** **domain** electromagnetic scattering problem with a kind of unbounded scatterer, that is, a locally perturbed perfectly electrical conducting plate. Speciﬁc **analysis** is provided for the perfectly electrical conducting boundary condition and Maxwell’s equations to accomplish the symmetric continuation, and a symmetric scattering problem with a bounded scatterer is obtained. To analyze the unique solvability and stability of **time** **domain** electromagnetic scattering problems, Fourier–Laplace transformation and a “Laplace **domain** to **time** **domain**” **analysis** are involved. A rigorous **analysis** implies the unique solvability and stability of the scattering problem with a locally perturbed plate and implies that the problem is equivalent to the symmetric scattering problem with a bounded scatterer.

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We have presented a method for **analysis** and synthesis of **time** signals using wavelet packet filtering techniques. From this study we could understand and experience the effectiveness of wavelet packet transform in **time** signal **analysis** and synthesis. The performance of wavelet packet is appreciable while comparing with the discrete wavelet transform decomposition technique since wave- let packet **analysis** can provide a more precise frequency resolution than the wavelet **analysis**. It also has compact support in **time** as well as in frequency **domain** and adapts its support locally to the signal which is important in **time** varying signal. With wavelet packets we have a greater variety of options for decomposing the signal. The method presented is used for **time** as well as frequency **analysis** of **time** varying signals. From the results we conclude that the wavelet filtering find applications in the **time** **domain** **analysis** and synthesis era. In terms of signal quality, Haar wavelet has been seen to be the best mother wavelet. This is taken from the **analysis** of the signal to noise ratio (SNR) value around which is quite satisfactory for **time** varying signals. The system has been tested with various sampling frequencies for **time** **domain** samples which gave satisfactory output. Taking into consideration the signal quality and the **time** for **analysis** and synthesis it can be concluded that Haar wavelet is the best mother wavelet. Hence we conclude that the system will behave stable with wavelet packet filter and can be used for **time** signal **analysis** and syn- thesis purpose.

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Typically the vibration **analysis** is carried out using techniques such as **time** **domain** **analysis**, frequency (spectral) **domain** **analysis**, order tracking **analysis**, **time** frequency **analysis**, **time** synchronous averaging, wavelet **analysis**, model based **analysis** etc. [5]. Fast Fourier Transformation (FFT) converts **time** **domain** signals into frequency **domain** signals and order **analysis** converts **time** **domain** signals into angular **domain** signals.

The **analysis** methods of HRV include **time** **domain** **analysis**, frequency **domain** **analysis** and nonlinear **analysis**. The high frequency components (HF) reflects the PNS level. The low frequency components (LF) is still controversial. It may only reflect the level of SNS and may also reflect SNS and PNS. The ratio of LF and HF (LF/HF) reflects the balance of SNS and PNS[10][11]. But research shows that HF and LF can be significantly affected by many factors. Therefore, it can’t only use these frequency **domain** parameters to analyze ANS. And this need to add index as circumstantial evidence[12]. Only using **time** **domain** or frequency **domain** **analysis** of HRV to analyze the modulation of ANS ignored the nonlinear characteristics of the HRV signal[13]. So this paper selected **time** **domain** parameters, frequency **domain** parameters and nonlinear parameters as the evaluation index. According to the AHP, the index system for evaluating ANS is presented in figure1.

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This paper introduced comparative **analysis** of blind audio source separation techniques in **time** **domain**, frequency **domain**. In **time** **domain** **analysis** modified convex divergence method and ICA decomposition techniques are considered and in frequency **domain** Inter-frequency Correlation with Microphone Diversity techniques are considered. To perform this **analysis** a critically determined system consists of three audio sources and three microphones are considered. Frequency **domain** **analysis** can be implemented for over determined mixture also, in that it extracts principle component to form a determined mixture. Simulations are performed on a closed room recording samples and convergence speed and complexity is compared. Result reflects that divergence based ICA overshadows the other competitors in terms of convergence speed and proved as a better audio source separation technique in blind scenario.

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In this paper, the concepts of speech processing algorithms for speech signal **analysis** is presented using the GUI model of MATLAB. Speech **analysis** is performed using short-**time** **analysis** to extract features in **time** **domain** and frequency **domain**. The short **time** **domain** **analysis** is useful for computing the **time** **domain** features like energy and zero crossing rate. The different frequency or spectral components that are present in the speech signal are not directly apparent in the **time** **domain**. Hence the frequency **domain** representation using Fourier representation is needed. The **time** varying nature of spectral information in speech leads to the need for short **time** of Fourier transform, termed more commonly as Short **time** Fourier Transform (STFT).The effect of different types of windows used in short **time** **analysis** with and without overlapping and the effect of window length in speech **analysis** are also demonstrated.

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This is, of course, nothing other than the brute dispute about phenomenology that I described earlier when I said that the B-theorist should simply reject the idea that it perceptually appears to us as though things are undergoing passage. Yet it is in fact Broad’s own observation that also provides the B-theorist with materials for a more substantive response at this stage. For she can use it to argue that the A- theorist’s idea that we can perceive the passage of **time** is grounded on a genuine insight into an aspect of the phenomenology of temporal awareness, but gets it wrong about what that aspect is. As Broad observes, sometimes, when we look at an object that is in fact moving, all we have are experiences of the object occupying different locations at different times, without us ever actually seeing the object moving. In cases of this sort, we can become aware of the movement only through the

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Abstract. The contribution describes a systematic method to efficiently determine frequency-**domain** electromagnetic antenna fields and characteristics for a broad spectrum via a single **time**-**domain** (e.g., Finite-Difference **Time**-**Domain**, FDTD) calculation. From a **time**-**domain** simulation of an antenna driven by a wide-band signal, a single modified Fourier transformation yields the frequency-**domain** multi- pole amplitudes. The corresponding multipole expansions are valid for the entire spectrum of the input pulse and at any point outside a minimum sphere enclosing the antenna. This allows a computationally cheap and elegant post-processing of arbitrary antenna characteristics. As an example of use the method is applied to determine high-resolution three- dimensional radiation patterns of an antipodal Vivaldi an- tenna.

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The square-root crack-tip shape-function describes the local behavior of the crack-opening-displacements (CODs) at crack-tips properly, and its use ensures an accurate[r]

The frequency **domain** is more compact and useful when we are dealing with more than one sine wave. For example, Figure 3.8 shows three sine waves, each with different amplitude and frequency. All can be represented by three spikes in the frequency **domain**.

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