Fast Frequency Estimation Research Articles

Fast and accurate haplotype frequency estimation for large haplotype vectors from pooled DNA data

BackgroundTypically, the first phase of a genome wide association study (GWAS) includes genotyping across hundreds of individuals and validation of the most significant SNPs. Allelotyping of pooled genomic DNA is a common approach to reduce the overall cost of the study. Knowledge of haplotype structure can provide additional information to single locus analyses. Several methods have been proposed for estimating haplotype frequencies in a population from pooled DNA data.ResultsWe introduce a technique for haplotype frequency estimation in a population from pooled DNA samples focusing on datasets containing a small number of individuals per pool (2 or 3 individuals) and a large number of markers. We compare our method with the publicly available state-of-the-art algorithms HIPPO and HAPLOPOOL on datasets of varying number of pools and marker sizes. We demonstrate that our algorithm provides improvements in terms of accuracy and computational time over competing methods for large number of markers while demonstrating comparable performance for smaller marker sizes. Our method is implemented in the "Tree-Based Deterministic Sampling Pool" (TDSPool) package which is available for download at http://www.ee.columbia.edu/~anastas/tdspool.ConclusionsUsing a tree-based determinstic sampling technique we present an algorithm for haplotype frequency estimation from pooled data. Our method demonstrates superior performance in datasets with large number of markers and could be the method of choice for haplotype frequency estimation in such datasets.

Correlation-based algorithm for multi-dimensional single-tone frequency estimation

In this paper, parameter estimation for a R-dimensional (R-D) single cisoid with R⩾2 in additive white Gaussian noise is addressed. By exploiting the correlation of the data samples, we construct R single-tone sequences which contain the R-D frequency parameters. Based on linear prediction and weighted linear squares techniques, two proposals are developed for fast and accurate frequency estimation from each constructed sequence. The two devised estimators are proved to be asymptotically unbiased while their variances achieve Cramér–Rao lower bound when the signal-to-noise ratio and/or data length tend to infinity. Computer simulations are also included to compare the proposed approach with conventional R-D harmonic retrieval schemes in terms of mean square error performance and computational complexity.

Fast frequency and harmonic estimation in power systems using a new optimized adaptive filter

This paper presents an adaptive filter for fast estimation of frequency and harmonic components of a power system voltage or current signal corrupted by noise with low signal to noise ratio (SNR). Unlike the conventional linear combiner (Adaline) approach, the new algorithm is based on an objective function often used in independent component analysis for robust tracking under impulse noise conditions. However, the accuracy and speed of convergence of this algorithm depend on the choice of step size of the filter and its adaptation. Instead of choosing the step size η and the parameter β of the cost function by trial and error, an adaptive particle swarm optimization technique is used alternatively to obtain both η and β to reduce the error between the observed voltage or current samples and the estimated ones. Using the optimized values, the amplitude and phase of the fundamental and harmonic components are estimated. Further, the extracted fundamental component is used to estimate any frequency drift of the power system recursively using an optimized error function obtained from three consecutive voltage samples. To test the effectiveness of the algorithm, several time-varying power system signals are simulated with harmonics, interharmonics, and decaying dc components buried in noise with low signal-to-noise ratio (SNR) and are used to estimate the frequency and harmonic components. This approach will be useful in islanding detection of a distributed generating system.

A fast, simple and accurate time-varying frequency estimation method for single-phase electric power systems

This paper presents a simple and accurate method to estimate time-varying frequency for single-phase electric power systems, based on three equally spaced samples. A sinusoidal voltage signal model, without dc offset, with time-varying frequency was assumed. Analytical formulas are derived. The method shows good estimation accuracy over a real world wide range of frequency changes. Simulations have been performed.

마이크로그리드 독립운전모드를 위한 주파수 추종에 관한 연구

This paper proposes a method for frequency control of islanded microgrid with battery energy storage system. For frequency control of islanded microgrid, battery energy storage system uses a phase locked loop algorithm with positive sequence components for a fast frequency estimation. Microgrid is a power system with small inertia because it has small capacity generators and inverter systems for renewable energy. So, Islanded microgrid`s frequency varies fast and large as small generation and load changes. To reduce frequency variation of islanded microgrid, it needs a device with fast frequency response. For fast frequency response, a fast frequency tracking is important. To show the validation of proposed fast frequency tracking algorithm, battery energy storage system with proposed algorithm is tested in microgrid pilot plant.

A new time‐domain based power system frequency estimation algorithm

SUMMARYFrequency stability is one of the most important features of power systems. It is closely dependent on the value of system frequency. In the present day modern power systems, fast and accurate frequency estimation has become quite vital. Any mistake in accurate estimation of frequency may threaten the frequency stability or at least lead to system operation problems. In this paper, a new time‐domain based power system frequency estimation algorithm is proposed. Different abnormal events such as frequency decline due to load‐generation mismatch are modeled and ability of the new frequency measurement technique to track the frequency is tested. Performance of the new method is evaluated and compared with an existing frequency estimation algorithm. Simulation results confirm advantages of the new approach over the existing method. Copyright © 2011 John Wiley & Sons, Ltd.

Subspace Approach for Fast and Accurate Single-Tone Frequency Estimation

A new signal subspace approach for estimating the frequency of a single complex tone in additive white noise is proposed in this correspondence. Our main ideas are to use a matrix without repeated elements to represent the observed signal and exploit the principal singular vectors of this matrix for frequency estimation. It is proved that for small error conditions, the frequency estimate is approximately unbiased and its variance is equal to Cramer-Rao lower bound. Computer simulations are included to compare the proposed approach with the generalized weighted linear predictor, periodogram, and phase-based maximum likelihood estimators in terms of estimation accuracy, computational complexity, and threshold performance.

Single Phase PWM Rectifier in Traction Application

Single Phase PWM Rectifier in Traction ApplicationThis research has been motivated by industrial demand for single phase PWM rectifier in traction application. This paper presents an advanced control structure design for a single phase PWM rectifier. The PWM rectifier is controlled to consume nearly sinusoidal current with power factor nearing to unity. The control structure consists of a DC-link voltage controller and a current controller implemented by a proportional-resonant controller using a fast phase angle and frequency estimator. The estimation algorithm is derived from the weighted least-squares estimation method. The feasibility of the proposed control structure is confirmed by experimental tests performed on designed laboratory prototype.

Application of a Combined Scheme for Estimating Power System Frequency from Distorted Signals

In present-day power systems, fast and accurate frequency estimation has become vital. Any mistake in accurate estimation of frequency could lead to system operation problems or system instability. Fast and accurate frequency estimation has become even more important due to the increasing level of harmonics and distortions and the need to be able to control the system more precisely. The level of system harmonics is increased in modern power systems. In addition, the presence of outside inference and noise coming from the environment and instruments are unavoidable. Accuracy of frequency estimation algorithms would be improved considerably if the effect of harmonics could be reduced and the signal noise diminished. In this article, a new combined scheme for estimating the frequency of a power system is presented and analyzed. The proposed method is based on a combination of the least square and zero crossing methods. An appropriate wavelet signal de-noising scheme is applied as well. Some post-processing units are also considered to modify the calculated results. The performance of the proposed scheme is evaluated using different data. Various tests using simulated samples and real data recorded from a power system are performed, and capabilities of the proposed algorithm are investigated. The obtained results confirm the capabilities of the proposed method.

Real-Time Estimation of Fundamental Frequency and Harmonics for Active Shunt Power Filters in Aircraft Electrical Systems

A novel algorithm for fundamental frequency and harmonic components detection is presented in this paper. The technique is based on a real-time implementation of discrete Fourier transform, and it allows fast and accurate estimation of fundamental frequency and harmonics of a distorted signal with variable fundamental frequency. It is suitable for active shunt filter applications, when fast and accurate tracking of the reference signal is required to achieve a good control performance. The main application for the algorithm is aircraft ac power systems, where the fundamental frequency can be either fixed on 400 Hz and its actual value fluctuates around the nominal value, or variable in the range 360-900 Hz. Hence, a real-time estimation of fundamental frequency is essential for active filter control. The proposed algorithm has been at first implemented in Matlab/Simulink for computer simulation, and it has been compared with a Phase Locked Loop (PLL) algorithm for frequency detection and the synchronous dq reference method for harmonic detection. Experimental tests have been carried out in order to validate the simulation results. The distorted current absorbed by a nonlinear load is analyzed and processed by means of a digital implementation of the algorithm running on the active shunt power filter control DSP, in order to calculate the active filter compensating current.

A New Adaptive Multiresolution Noise-Filtering Approach for SAR Interferometric Phase Images

This letter presents a novel adaptive multiresolution technique to estimate the local fringe frequency in synthetic aperture radar (SAR) interferometric phase images. According to the coherent summation principle, the size and the shape of the interferogram spatial resolution for local frequency estimation are adapted pixel by pixel to track the topographic changes and optimize the space-frequency resolution. We show that, comparing conventional filters with the processing window of a fixed size (such as 7 times 7) and shape (such as a square), the proposed approach avoids the loss of phase fringes and provides a more accurate representation of the scene topography. In this letter, we present a method to eliminate invalid frequency estimation. A fast frequency estimation approach modified from the method proposed by Trouve et al. is also shown. Finally, both simulated data and actual SAR data are utilized to illustrate the effectiveness of the proposed method.

Further result in the fast and accurate estimation of single frequency

A new fast and accurate method for estimating the frequency of a complex sinusoid in complex white Gaussian environments is proposed. The new estimator comprises of applications of low-pass filtering, decimation, and frequency estimation by linear prediction. It is computationally efficient yet obtains the Cramer-Rao bound at moderate signal-to-noise ratios. And it is well suited for real time applications requiring precise frequency estimation. Simulation results are included to demonstrate the performance of the proposed method.

A fast on-line frequency estimator of lightly damped vibrations in flexible structures

A significant research effort has been conducted in the past to achieve a reliable on-line vibration mode estimator. Frequently, pure sinusoidal models of the underlying mechanical system have been used to accomplish the estimation task. In this paper, an algebraic approach is proposed for the fast and reliable, on-line identification of the natural frequency of a flexible-link manipulator. The proposed method uses the pure sinusoidal model in combination with the algebraic derivative method for parameter identification. The method leads, in the time domain, to an exact computation formulae for the unknown frequency parameter. This formula is synthesized in terms of time-varying linear unstable filters in combination with classical low-pass filters of the Butterworth type. The computations are performed in a quite small-time interval which is only a small fraction of the first full cycle of the measured sinusoidal signal. The proposed method is verified to be robust with respect to un-modeled small attenuations, present in the flexible structure, and to measurement noise. An experimental setup has been developed as a benchmark to test and compare the proposed method with other recently developed parameter estimation techniques.

MAP/ML Estimation of the Frequency and Phase of a Single Sinusoid in Noise

The problem of estimating the frequency and carrier phase of a single sinusoid observed in additive, white, Gaussian noise is addressed. Much of the work in the literature considers maximum likelihood (ML) estimation. However, the ML estimator given by the location of the peak of a periodogram in the frequency domain shown in D.C. Rife and R. R. Boorstyn, Single-tone parameter estimation from discrete-time observations, IEEE Transactions on Information Theory, vol. IT-20, pp. 591-598, Sep. 1974, has a very high computational complexity. This paper derives the explicit structure of the ML estimator for data processing in the time domain, assuming only reasonably high signal-to-noise ratio (SNR). The result of this approximate ML estimator shows that both the phase and the magnitude of the noisy signal samples are utilized in the and the phase data alone as assumed in S. A. Tretter, Estimating the frequency of a noisy sinusoid by linear regression, IEEE Transactions on Information Theory, vol. IT-31, pp. 832-835, Nov. 1985 and S. Kay, A fast and accurate single frequency estimator, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 39, pp. 1203-1205, May 1991, is not a sufficient statistic. The sample-by-sample iterative processing nature of the estimator enables us to propose a novel, recursive phase-unwrapping algorithm that allows the estimator to be implemented efficiently. To facilitate the performance analysis, a new, linearized observation model for the instantaneous signal phase that is more accurate than that of S. A. Tretter, Estimating the frequency of a noisy sinusoid by linear regression, IEEE Transactions on Information Theory, vol. IT-31, pp. 832-835, Nov. 1985 and of S. Kay, A fast and accurate single frequency estimator, vol. 39, pp. 1203-1205, May 1991, is proposed. This new model explains physically why the phase data are weighted by the magnitude information in the ML estimator. Moreover, by incorporating a priori knowledge via the a priori probability density function of the unknown frequency and the carrier phase, the explicit structure of the approximate maximum a posteriori probability (MAP) estimator is derived, and the Bayesian Cramer-Rao lower bound (BCRLB) on the mean-square error (mse) is obtained. Our analysis shows that the mse performance of the MAP estimator can approach the BCRLB very closely

A fast and accurate frequency estimation method for canceling harmonic noise in geophysical records

The cancellation of harmonic noise from geophysical records can be achieved by subtracting an estimate of the harmonic noise. Estimating the harmonic noise consists of estimating the fundamental frequency and the amplitudes and phases of all harmonics. We propose a new frequency-estimation method that builds upon the estimator originally proposed by Nyman and Gaiser. This Nyman and Gaiser estimation (NGE) method exploits the fact that the noise fundamental frequency is known to be close to 60 Hz. The NGE method is based on solving a system of four equations that determine the amplitude, phase, and frequency of a given harmonic in the harmonic noise. Hence, NGE can produce frequency estimates for all harmonics. Our improved estimator uses a suitable linear combination of these NGE frequency estimates to produce a more accurate estimate of the fundamental frequency. Our method is more accurate than NGE, and its accuracy is comparable to least-squares estimation (LSE). The advantage of our method is that it is about two times faster than LSE. This speed gain can become valuable when processing large magnetotelluric (MT) data records. Applying our method to the restoration of MT data, we found that the harmonic noise amplitude in the periodogram is reduced by at least 60 dB to a level below that of MT data.

A novel algorithm in the FMCW microwave liquid level measuring system

The structure of a frequency modulated continuous wave (FMCW) microwave liquid level radar system was introduced and the FMCW radar ranging principle was discussed. A fast frequency estimation algorithm (FFEA) based on fast Fourier transform (FFT) technique, which can achieve high ranging accuracy and better computational efficiency, was proposed to obtain the distance information from the radar echo signal. The high-speed signal processor DSP is suitable for the real-time signal processing, and can be used to linearize the frequency sweep of VCO. The simulation results indicated that FFEA owned high accuracy as compared with the FFT method and required much less computational load as compared with zoom FFT.

Fast Frequency Estimation by Zero Crossings of Differential Spline Wavelet Transform

Zero crossings or extrema of a wavelet transform constitute important signatures for signal analysis with the advantage of great simplicity. In this paper, we introduce a fast frequency-estimation method based on zero-crossing counting in the transform domain of a family of differential spline wavelets. The resolution and order of the vanishing moments of the chosen wavelets have a close relation with the frequency components of a signal. Theoretical results on estimating the highest and the lowest frequency components are derived, which are particularly useful for frequency estimation of harmonic signals. The results are illustrated with the help of several numerical examples. Finally, we discuss the connection of this approach with other frequency estimation methods, with the high-order level-crossing analysis in statistics, and with the scaling theorem in computer vision.

New technique for frequency and amplitude estimation of power system signals

This paper describes the design, analysis and computational aspects of a technique for the measurement of power system voltage, current and frequency. This technique can be used in a digital AVR for the state estimation of turbine-generator terminal quantities or in a digital relay for protection of a power system. This technique provides fast and accurate estimation of power system frequency, and is used in a Kalman-filtering algorithm to estimate power system voltage and current signals. Practical considerations such as the effect of power system harmonics, noise, frequency changes, mechanical and electrical load changes are taken into account during implementation of this technique. Several computer simulation tests are presented to highlight the usefulness of the technique. Simulation results show that the technique can simultaneously estimate the amplitude and frequency of a sinusoidal signal, even in the case that the signal is distorted by harmonics or noise or encounters frequency changes.

Fast and accurate single frequency estimator

A new fast and accurate method for estimating the frequency of a complex sinusoid in complex white Gaussian noise is proposed. The proposed estimator has the lowest computational complexity among the estimators. Its performance and estimation range are similar to the Fitz and L&R estimators, and its threshold is 20 log(m) less than the Kay estimator.

03/02358 Wide-range, fast and robust estimation of power system frequency: Karimi-Ghartemani, M. and Iravani, M. R. Electric Power Systems Research, 2003, 65, (2), 109–117

03/02358 Wide-range, fast and robust estimation of power system frequency: Karimi-Ghartemani, M. and Iravani, M. R. Electric Power Systems Research, 2003, 65, (2), 109–117