Time Domain

Fruit thinning has been practised for thousand of years, and serves a number of purposes. Too many fruits per tree can result in small fruit size and poor quality, breakage of limbs, exhaustion of tree reserves, and can also partially o completely inhibit bud initiation. Hand thinning of the peaches is the most common thinning practice adopted, but it is

The numerical implementation of the Direct Boundary Element formulation for time-domain transient analysis of three-dimensional solids is presented in a most general and complete manner. The present formulation employs the space and time dependent fundamental solution (Stokes' solution) and Graffi's dynamic reciprocal theorem to derive the boundary integral equations in the time domain. A time-stepping scheme is then used to solve the boundary initial value problem by marching forward in time. Higher order shape functions are used to approximate the field quantities in space as well as in time, and a combination of analytical (time-integration) and numerical (spatial-integration) integration is carried out to form a system of linear equations. At the end of each time step, these equations are solved to obtain the unknown field quantities at that time.Finally, the accuracy and reliability of this algorithm is demonstrated by solving a number of example problems and comparing the results against the available analytical and numerical solution.

We propose the audio inpainting framework that recovers portions of audio data distorted due to impairments such as impulsive noise, clipping, and packet loss. In this framework, the distorted data are treated as missing and their location is assumed to be known. The signal is decomposed into overlapping time-domain frames and the restoration problem is then formulated as an inverse problem per audio frame. Sparse representation modeling is employed per frame, and each inverse problem is solved using the Orthogonal Matching Pursuit algorithm together with a discrete cosine or a Gabor dictionary. The Signal-to-Noise Ratio performance of this algorithm is shown to be comparable or better than state-of-the-art methods when blocks of samples of variable durations are missing. We also demonstrate that the size of the block of missing samples, rather than the overall number of missing samples, is a crucial parameter for high quality signal restoration. We further introduce a constrained Matching Pursuit approach for the special case of audio declipping that exploits the sign pattern of clipped audio samples and their maximal absolute value, as well as allowing the user to specify the maximum amplitude of the signal. This approach is shown to outperform state-of-the-art and commercially available methods for audio declipping in terms of Signal-to-Noise Ratio.

Machine condition monitoring plays an important role in industry to ensure the continuity of the process. This work presents a simple and yet, fast approach to detect simultaneous machinery faults using sound mixture emitted by machines. We developed a microphone array as the sensor. By exploiting the independency of each individual signal, we estimated the mixture of the signals and compared time-domain independent component analysis (TDICA), frequency-domain independent component analysis (FDICA) and Multi-stage ICA. In this research, four fault conditions commonly occurred in industry were evaluated, namely normal (as baseline), unbalance, misalignment and bearing fault. The results showed that the best separation process by SNR criterion was time-domain ICA. At the final stage, the separated signal was analyzed using Instantaneous Frequency technique to determine the exact location of the frequency at the specific time better than spectrogram.

Using time-domain Terahertz spectroscopy we performed direct studies of the photoinduced suppression and recovery of the superconducting gap in a conventional BCS superconductor. Both processes are found to be strongly temperature and excitation density dependent. The analysis of the data with the established phenomenological Rothwarf-Taylor model enabled us to determine the bare recombination rate of quasiparticles, the Cooper pair-breaking rate and the electron-phonon coupling constant, $\lambda=1.1\pm0.1,$ which is in excellent agreement with theoretical estimates.

Purpose: In the present work was made the comparative analysis in time domain and frequency domain to the acoustical pressure generate by the electric arc to determinate which of the two analysis methods is better to evaluates the stability in GMAW process. Design/methodology/approach: Welds had been made with the parameters adjusted to get the highest stability. In these conditions, were

A simple non-quasi-static small-signal equivalent circuit model is derived for the ideal MOSFET wave equation under the gradual channel approximation. This equivalent circuit represents each Y-parameter by its DC small-signal value shunted by a (trans) capacitor in series with a charging (trans) resistor. A large-signal model for the intrinsic MOSFET is derived by first implementing this RC topology in the

In this article, we demonstrate an energy efficient convolutional neural network (CNN) engine by performing the multiply-and-accumulate (MAC) operations in the time domain. The multi-bit inputs are compactly represented as a single pulse width encoded input. This translates into reduced switching capacitance (CDYN), compared to baseline digital implementation, and can enable low power neural network computing in an edge device. The time-domain CNN engine employs a novel bi-directional memory delay line (MDL) unit to perform signed accumulation of input and weight products. The proposed MDL design leverages standard digital circuits and does not require any capacitors and complex analog-to-digital converters (ADCs) to realize the convolution operation, thereby enabling easy scaling across the process technology nodes. Four speed-up modes and a configurable MDL length are supported to address throughput versus accuracy trade-off of the time-domain computing approach. Delay calibration units have been accommodated to mitigate the process variation induced delay mismatch among concurrently operating MDL units. The proposed time-domain MDL design implements a LeNet-5 CNN engine in a commercial 40-nm CMOS process achieving energy efficiency of 12.08 TOPS/W, a throughput of 0.365 GOPS at 537 mV in the 16× speed-up mode. 40-nm CMOS test-chip measurements over 100 MNIST images show 97% classification accuracy. Simulation results over the entire 10000 MNIST validation dataset images taking into account the circuit non-ideal effects of the MDL-based time-domain approach show a classification accuracy of 98.42%. The test-chip is operational down to the near-threshold voltage (up to 375 mV) while maintaining the classification accuracy over 90% in the 1× speed-up mode. Furthermore, two methods of scaling MDLs to multi-bit weights are proposed. Simulation results for 1000-class AlexNet over 50000 ImageNet validation dataset images show classification accuracy loss within 1% when compared with software implementation.

Synthesis and photophysical studies of (O-methyl)-ß-tyrosine (ß-tyrosine; an analogue of tyrosine, in which the amino group is moved from the a-to the ß-carbon, closer to the phenol ring) and its derivatives with a blocked amino and/or carboxyl group were performed to ...

This paper introduces and evaluates the use of Gaussian mixture models (GMMs) for multiple limb motion classification using continuous myoelectric signals. The focus of this work is to optimize the configuration of this classification scheme. To that end, a complete experimental evaluation of this system is conducted on a 12 subject database. The experiments examine the GMMs algorithmic issues including the model order selection and variance limiting, the segmentation of the data, and various feature sets including time-domain features and autoregressive features. The benefits of postprocessing the results using a majority vote rule are demonstrated. The performance of the GMM is compared to three commonly used classifiers: a linear discriminant analysis, a linear perceptron network, and a multilayer perceptron neural network. The GMM-based limb motion classification system demonstrates exceptional classification accuracy and results in a robust method of motion classification with low computational load.

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time domain, are obtained. Next, a LPV model with linear fractional dependence (LFR) with respect to measured variables is fitted with the condition of containing all the linear models identified in previous step (differential inclusion). The fit is carried out using nonlinear least squares algorithms. Finally, this identification methodology will then be applied to a nonlinear turbocharged diesel engine.

As far as we are concerned, the implementation of the finite differences in the time domain (FDTD) method requires, for the solutions of several practical problems in electromagnetism, a long process time and a large amount of memory, what makes it impracticable in various cases, principally when the serial process is used. The current work deals with the conception of a Beowulf cluster and it aims to implement the FDTD method using parallel process for the study of antennas. The obtained system efficiency is then tested in the analysis of a monopole antenna, what is done by comparing the time spent in the parallel and serial processing.

From a comparison of the photoresponses and membrane properties of photoreceptors from 20 species of Diptera, we conclude that coding in the time domain is matched to the dictates of visual ecology. This matching involves the dynamics of phototransduction and the use of an appropriate mix of potassium conductances to tune the photoreceptor membrane. Rapidly flying, manoeuvrable diurnal Diptera from several families have fast photoreceptors, with corner frequencies (the frequency at which signal power falls by a half) of between 50 and 107 Hz. The ponderous and predominantly nocturnal tipulids have slow photoreceptors with fully light adapted corner frequencies of 16 to 19 Hz. Dark adapted fast photoreceptors have a lower gain (as indicated by lower noise levels), a lower sensitivity, and light adapt more rapidly than dark adapted slow photoreceptors. Fast cells also have much lower input resistances and shorter time constants. Fast photoreceptors rectify more strongly in the steady state because of a weakly inactivating delayed rectifier potassium conductance with fast and slow components of activation. Slow photoreceptors rectify less strongly in the steady state because their membrane properties are dominated by strongly inactivating outward currents with reversal potentials in the range — 80 to -90 mV. The differences between potassium conductances match the differing functional requirements of fast and slow photoreceptors. The non-inactivating delayed rectifier promotes the rapid response of fast cells by reducing the membrane time constant. This is an expensive strategy, involving large conductances and currents. Slowly flying nocturnal insects do not require a high speed of response. The potassium conductances in their slow photoreceptors inactivate to avoid costly and unnecessary ion fluxes. Both the dynamics of the photoresponse and photoreceptor membrane properties exhibit sexual dimorphism. Light adapted photoreceptors in the enlarged male dorsal eye of Bibio markii have a corner frequency of 42 Hz, compared with 27 Hz for cells in the smaller female eye. This difference in frequency response correlates with the male's higher spatial acuity and is accompanied by consistent differences in potassium conductance activation rate. We conclude that the divison between fast and slow cells is the product of cellular constraints, metabolic costs and the requirements of coding efficiency at different light levels and retinal image velocities.