Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pos...Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.展开更多
The reflectometry is a common method used to measure the thickness of thin films. Using a conventional method,its measurable range is limited due to the low resolution of the current spectrometer embedded in the refle...The reflectometry is a common method used to measure the thickness of thin films. Using a conventional method,its measurable range is limited due to the low resolution of the current spectrometer embedded in the reflectometer.We present a simple method, using cubic spline interpolation to resample the spectrum with a high resolution,to extend the measurable transparent film thickness. A large measuring range up to 385 m in optical thickness is achieved with the commonly used system. The numerical calculation and experimental results demonstrate that using the FFT method combined with cubic spline interpolation resampling in reflectrometry, a simple,easy-to-operate, economic measuring system can be achieved with high measuring accuracy and replicability.展开更多
This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic d...This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic data obtained from the Tano Basin in West Africa, Ghana. The research focuses on a comparative analysis of image clarity in seismic attribute analysis to facilitate the identification of reservoir features within the subsurface structures. The findings of the study indicate that CWT has a significant advantage over FFT in terms of image quality and identifying subsurface structures. The results demonstrate the superior performance of CWT in providing a better representation, making it more effective for seismic attribute analysis. The study highlights the importance of choosing the appropriate image enhancement technique based on the specific application needs and the broader context of the study. While CWT provides high-quality images and superior performance in identifying subsurface structures, the selection between these methods should be made judiciously, taking into account the objectives of the study and the characteristics of the signals being analyzed. The research provides valuable insights into the decision-making process for selecting image enhancement techniques in seismic data analysis, helping researchers and practitioners make informed choices that cater to the unique requirements of their studies. Ultimately, this study contributes to the advancement of the field of subsurface imaging and geological feature identification.展开更多
Cardiac Arrhythmias shows a condition of abnor-mal electrical activity in the heart which is a threat to humans. This paper presents a method to analyze electrocardiogram (ECG) signal, extract the fea-tures, for the c...Cardiac Arrhythmias shows a condition of abnor-mal electrical activity in the heart which is a threat to humans. This paper presents a method to analyze electrocardiogram (ECG) signal, extract the fea-tures, for the classification of heart beats according to different arrhythmias. Data were obtained from 40 records of the MIT-BIH arrhythmia database (only one lead). Cardiac arrhythmias which are found are Tachycardia, Bradycardia, Supraventricular Tachycardia, Incomplete Bundle Branch Block, Bundle Branch Block, Ventricular Tachycardia. A learning dataset for the neural network was obtained from a twenty records set which were manually classified using MIT-BIH Arrhythmia Database Directory and docu- mentation, taking advantage of the professional experience of a cardiologist. Fast Fourier transforms are used to identify the peaks in the ECG signal and then Neural Networks are applied to identify the diseases. Levenberg Marquardt Back-Propagation algorithm is used to train the network. The results obtained have better efficiency then the previously proposed methods.展开更多
In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be a...In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be able to achieve acquisition in a very short time in spite of large Doppler frequencies. However, the traditional methods cannot solve it well. This work describes a new method that uses a differential decoding technique for Doppler mitigation and a batch process of FFT (fast Fourier transform) and IFFT (invert FFT) for the purpose of parallel code phase search by frequency domain correlation. After the code phase is estimated, another FFT process is carried out to search the Doppler frequency. Since both code phase and Doppler frequency domains are searched in parallel, this architecture can provide acquisition fifty times faster than conventional FFT methods. The performance in terms of the probability of detection and false alarm are also analyzed and simulated, showing that a signal-to-noise ratio (SNR) loss of 3 dB is introduced by the differential decoding. The proposed method is an efficient way to shorten the acquisition time with slightly hardware increasing.展开更多
The traditional orthogonal frequency divi-sion multiplexing(OFDM)transmitter is implemented by inverse fast Fourier transform(IFFT),up-sampling and low pass shaping filter(LPSF),which occupy a large number of hardware...The traditional orthogonal frequency divi-sion multiplexing(OFDM)transmitter is implemented by inverse fast Fourier transform(IFFT),up-sampling and low pass shaping filter(LPSF),which occupy a large number of hardware resources and have long la-tency.To further meet the 5G and future 6G commu-nication requirements,this paper proposes a novel di-rect digital synthesis(DDS)based OFDM transmitter structure that can replace these modules.Due to the strong parallelism of the system structure,it is very suitable for implementation on field programable gate array(FPGA)platform.After making two special sim-plifications to the primary structure,the refined struc-ture becomes very simple compared with the tradi-tional structures.Most attractively,the proposed struc-ture has the following three advantages that i)the data transformation from frequency domain to time domain has zero latency,ii)the transformation length does not need to be an integer power of 2 and iii)the struc-ture does not even need to use any multiplier,thus leading to low implementation complexity and high speed.Comparative experiments are carried out on Intel FPGA platform which show that our DDS based structure can save more than half of the resources com-pared with the traditional structures and can provide the same bit error rate(BER)performance under the condition without using any LPSF.展开更多
In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and freq...In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has become a particularly challenging topic.To solve this issue,this paper proposes an improved spectrum analysis method by improving the window function and a spectrum correction method to achieve higher precision.First,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-convolved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO modes.Subsequently,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window function is proposed to estimate the parameters of SsO.This method allows for phase-unbiased estimation while maintaining algorithmic simplicity and expedience.The performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation methods.Simulation results validate the effectiveness and superiority of the proposed method.展开更多
A Fast Fourier transform approach has been presented by Carr & Madan (2009) on a single underlying asset. In this current research paper, we present fast Fourier transform algorithm for the valuation of Multi-asse...A Fast Fourier transform approach has been presented by Carr & Madan (2009) on a single underlying asset. In this current research paper, we present fast Fourier transform algorithm for the valuation of Multi-asset Options under Economic Recession Induced Uncertainties. The issue of multi-dimension in both finite and infinite case of Options is part of the focus of this research. The notion of economic recession was incorporated. An intuition behind the introduction of recession induced volatility uncertainty is revealed by huge volatility variation during the period of economic recession compared to the period of recession-free. Nigeria economic recession outbreak in 2016 and its effects on the uncertainty of the payoffs of Nigeria Stocks Exchange (NSE) among other investments was among the motivating factors for proposing economic recession induced volatility in options pricing. The application of the proposed Fast Fourier Transform algorithm in handling multi-assets options was shown. A new result on options pricing was achieved and capable of yielding efficient option prices during and out of recession. Numerical results were presented on assets in 3-dimensions as an illustration taking Black Scholes prices as a bench mark for method effectiveness comparison. The key findings of this research paper among other crucial contributions could be seen in computational procedure of options valuation in multi-dimensions and uncertainties in options payoffs under the exposure of economic recession.展开更多
文摘Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.
基金Supported by the National Natural Science Foundation of China under Grant No 11604115the Educational Commission of Jiangsu Province of China under Grant No 17KJA460004the Huaian Science and Technology Funds under Grant No HAC201701
文摘The reflectometry is a common method used to measure the thickness of thin films. Using a conventional method,its measurable range is limited due to the low resolution of the current spectrometer embedded in the reflectometer.We present a simple method, using cubic spline interpolation to resample the spectrum with a high resolution,to extend the measurable transparent film thickness. A large measuring range up to 385 m in optical thickness is achieved with the commonly used system. The numerical calculation and experimental results demonstrate that using the FFT method combined with cubic spline interpolation resampling in reflectrometry, a simple,easy-to-operate, economic measuring system can be achieved with high measuring accuracy and replicability.
文摘This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic data obtained from the Tano Basin in West Africa, Ghana. The research focuses on a comparative analysis of image clarity in seismic attribute analysis to facilitate the identification of reservoir features within the subsurface structures. The findings of the study indicate that CWT has a significant advantage over FFT in terms of image quality and identifying subsurface structures. The results demonstrate the superior performance of CWT in providing a better representation, making it more effective for seismic attribute analysis. The study highlights the importance of choosing the appropriate image enhancement technique based on the specific application needs and the broader context of the study. While CWT provides high-quality images and superior performance in identifying subsurface structures, the selection between these methods should be made judiciously, taking into account the objectives of the study and the characteristics of the signals being analyzed. The research provides valuable insights into the decision-making process for selecting image enhancement techniques in seismic data analysis, helping researchers and practitioners make informed choices that cater to the unique requirements of their studies. Ultimately, this study contributes to the advancement of the field of subsurface imaging and geological feature identification.
文摘Cardiac Arrhythmias shows a condition of abnor-mal electrical activity in the heart which is a threat to humans. This paper presents a method to analyze electrocardiogram (ECG) signal, extract the fea-tures, for the classification of heart beats according to different arrhythmias. Data were obtained from 40 records of the MIT-BIH arrhythmia database (only one lead). Cardiac arrhythmias which are found are Tachycardia, Bradycardia, Supraventricular Tachycardia, Incomplete Bundle Branch Block, Bundle Branch Block, Ventricular Tachycardia. A learning dataset for the neural network was obtained from a twenty records set which were manually classified using MIT-BIH Arrhythmia Database Directory and docu- mentation, taking advantage of the professional experience of a cardiologist. Fast Fourier transforms are used to identify the peaks in the ECG signal and then Neural Networks are applied to identify the diseases. Levenberg Marquardt Back-Propagation algorithm is used to train the network. The results obtained have better efficiency then the previously proposed methods.
基金Project(60904090) supported by the National Natural Science Foundation of China
文摘In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be able to achieve acquisition in a very short time in spite of large Doppler frequencies. However, the traditional methods cannot solve it well. This work describes a new method that uses a differential decoding technique for Doppler mitigation and a batch process of FFT (fast Fourier transform) and IFFT (invert FFT) for the purpose of parallel code phase search by frequency domain correlation. After the code phase is estimated, another FFT process is carried out to search the Doppler frequency. Since both code phase and Doppler frequency domains are searched in parallel, this architecture can provide acquisition fifty times faster than conventional FFT methods. The performance in terms of the probability of detection and false alarm are also analyzed and simulated, showing that a signal-to-noise ratio (SNR) loss of 3 dB is introduced by the differential decoding. The proposed method is an efficient way to shorten the acquisition time with slightly hardware increasing.
基金the Natural Science Foun-dation of Hubei Province under Grant 2019CFB593National Natural Science Foundation of China un-der Grant 61961016Starting Fund for Doc-toral Research in Hubei Minzu University under Grant MY2018B018.
文摘The traditional orthogonal frequency divi-sion multiplexing(OFDM)transmitter is implemented by inverse fast Fourier transform(IFFT),up-sampling and low pass shaping filter(LPSF),which occupy a large number of hardware resources and have long la-tency.To further meet the 5G and future 6G commu-nication requirements,this paper proposes a novel di-rect digital synthesis(DDS)based OFDM transmitter structure that can replace these modules.Due to the strong parallelism of the system structure,it is very suitable for implementation on field programable gate array(FPGA)platform.After making two special sim-plifications to the primary structure,the refined struc-ture becomes very simple compared with the tradi-tional structures.Most attractively,the proposed struc-ture has the following three advantages that i)the data transformation from frequency domain to time domain has zero latency,ii)the transformation length does not need to be an integer power of 2 and iii)the struc-ture does not even need to use any multiplier,thus leading to low implementation complexity and high speed.Comparative experiments are carried out on Intel FPGA platform which show that our DDS based structure can save more than half of the resources com-pared with the traditional structures and can provide the same bit error rate(BER)performance under the condition without using any LPSF.
基金supported in part by Science and Technology Project of State Grid Corporation of China(No.5108-202299269A-1-0-ZB).
文摘In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has become a particularly challenging topic.To solve this issue,this paper proposes an improved spectrum analysis method by improving the window function and a spectrum correction method to achieve higher precision.First,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-convolved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO modes.Subsequently,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window function is proposed to estimate the parameters of SsO.This method allows for phase-unbiased estimation while maintaining algorithmic simplicity and expedience.The performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation methods.Simulation results validate the effectiveness and superiority of the proposed method.
文摘A Fast Fourier transform approach has been presented by Carr & Madan (2009) on a single underlying asset. In this current research paper, we present fast Fourier transform algorithm for the valuation of Multi-asset Options under Economic Recession Induced Uncertainties. The issue of multi-dimension in both finite and infinite case of Options is part of the focus of this research. The notion of economic recession was incorporated. An intuition behind the introduction of recession induced volatility uncertainty is revealed by huge volatility variation during the period of economic recession compared to the period of recession-free. Nigeria economic recession outbreak in 2016 and its effects on the uncertainty of the payoffs of Nigeria Stocks Exchange (NSE) among other investments was among the motivating factors for proposing economic recession induced volatility in options pricing. The application of the proposed Fast Fourier Transform algorithm in handling multi-assets options was shown. A new result on options pricing was achieved and capable of yielding efficient option prices during and out of recession. Numerical results were presented on assets in 3-dimensions as an illustration taking Black Scholes prices as a bench mark for method effectiveness comparison. The key findings of this research paper among other crucial contributions could be seen in computational procedure of options valuation in multi-dimensions and uncertainties in options payoffs under the exposure of economic recession.