Nabeel Khan | GMV - Academia.edu (original) (raw)

Papers by Nabeel Khan

Turkish Journal of Electrical Engineering and Computer Sciences, May 1, 2022

In order to recover missing samples in a nonstationary signal, this paper employs a time-signal a... more In order to recover missing samples in a nonstationary signal, this paper employs a time-signal analysis and filtering method. The instantaneous frequency of a multicomponent signal is first estimated by employing a robust and computationally efficient method. Then the time-frequency filtering is performed using a dechirping operation to recover missing samples. These steps are repeated until convergence. The proposed method achieves better performance than the state of art methods both in terms of the accuracy of the recovered signal and computational efficiency.

Entropy, Mar 25, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

International Journal of Adaptive Control and Signal Processing, Jul 1, 2015

A novel method is presented for the instantaneous frequency estimation of multi-component signals... more A novel method is presented for the instantaneous frequency estimation of multi-component signals with crossing signatures in the time-frequency domain. The proposed method uses a combination of Eigen decomposition of time-frequency distributions and time-frequency filtering to recursively extract signal components from the original mixture and estimate their instantaneous frequencies. The proposed algorithm outperforms other algorithms of similar complexity in terms of mean square error accuracy.

Digital Signal Processing, Aug 1, 2023

Research Square (Research Square), Jan 6, 2023

In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorith... more In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorithm for the reconstruction of missing samples. The proposed IF estimation and sparse reconstruction algorithm is developed by adding a refinement step where the crude estimates of IFs and signal components are further improved through the reestimation stage. During the re-estimation stage, both IFs, as well as the signal components, are re-estimated by removing all the remaining components. Experimental results indicate that the proposed strategy improves both the accuracy of IF estimates as well as missing samples.

Research Square (Research Square), Dec 20, 2022

In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorith... more In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorithm for the reconstruction of missing samples. The proposed IF estimation and sparse reconstruction algorithm is developed by adding a refinement step where the crude estimates of IFs and signal components are further improved through the reestimation stage. During the re-estimation stage, both IFs, as well as the signal components, are re-estimated by removing all the remaining components. Experimental results indicate that the proposed strategy improves both the accuracy of IF estimates as well as missing samples.

Multidimensional Systems and Signal Processing, Feb 26, 2022

IEEE Signal Processing Letters, Feb 1, 2013

Circuits Systems and Signal Processing, Jan 5, 2023

Adaptive directional time-frequency distribution (ADTFD) is an efficient TFD, which has outperfor... more Adaptive directional time-frequency distribution (ADTFD) is an efficient TFD, which has outperformed most of the adaptive and fixed TFDs. The ADTFD locally optimizes the direction of the smoothing kernel on the basis of directional Gaussian or double derivative directional Gaussian filter (DGF). However, high computation cost of ADTFD has made this method inconvenient for processing real-life signals, i.e, biomedical signals. This paper addresses this problem and introduces a low-cost ADTFD with much lower computation cost and approximately similar efficiency of ADTFD. In the proposed method, instead of iterative filtering in different directions, which is computationally expensive, the optimized directions are estimated using the Radon transform of the modulus of the signal's ambiguity function. The results show that the proposed method is much faster than the ADTFD.

Sensors, Apr 15, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Circuits, Systems, and Signal Processing

2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI), 2017

Spikes are one of the main characteristics of a seizure electroencephalogram (EEG) signal. This f... more Spikes are one of the main characteristics of a seizure electroencephalogram (EEG) signal. This feature plays an important role in seizure abnormality detection in EEG signals. The objective of this work is to provide a methodology to enhance this characteristic in the time-frequency domain. To achieve this goal first, we amplify the spike components in the raw EEG signal using the differential window, then a modified version of adaptive directional time-frequency distribution of the amplified signal is computed. The performance of the proposed method assessed using a simulated and a real EEG data. The results show an improvement in the time-frequency representations of a signal with spikes components. Different TFDs are tested, the modified-ADTFD provides the best performance among the selected TFDs.

Signal, Image and Video Processing, 2021

This paper presents a computational efficient method to estimate the IF of multi-component signal... more This paper presents a computational efficient method to estimate the IF of multi-component signals for both mono-sensor and multi-sensor recordings. The algorithm uses fractional Fourier windows to find out both the highest energy TF point and the optimal rotation order of the analysis window at that point. The detected peak and rotation order are then used to track the IF curve by using linear interpolation to skip a predetermined number of samples, thus reducing the computational cost. The estimated IF is then used to remove the strongest component from the mixture, and this process is repeated till IFs of all the components are estimated. Experimental results indicate that the proposed method achieves similar performance in terms of the accuracy of IF estimate as that of the state-of-the-art method while significantly reducing the computational cost.

Social Science Research Network, 2022

Signal Processing, May 1, 2023

Signal, Image and Video Processing

Turkish Journal of Electrical Engineering and Computer Sciences, May 1, 2022

In order to recover missing samples in a nonstationary signal, this paper employs a time-signal a... more In order to recover missing samples in a nonstationary signal, this paper employs a time-signal analysis and filtering method. The instantaneous frequency of a multicomponent signal is first estimated by employing a robust and computationally efficient method. Then the time-frequency filtering is performed using a dechirping operation to recover missing samples. These steps are repeated until convergence. The proposed method achieves better performance than the state of art methods both in terms of the accuracy of the recovered signal and computational efficiency.

Entropy, Mar 25, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

International Journal of Adaptive Control and Signal Processing, Jul 1, 2015

A novel method is presented for the instantaneous frequency estimation of multi-component signals... more A novel method is presented for the instantaneous frequency estimation of multi-component signals with crossing signatures in the time-frequency domain. The proposed method uses a combination of Eigen decomposition of time-frequency distributions and time-frequency filtering to recursively extract signal components from the original mixture and estimate their instantaneous frequencies. The proposed algorithm outperforms other algorithms of similar complexity in terms of mean square error accuracy.

Digital Signal Processing, Aug 1, 2023

Research Square (Research Square), Jan 6, 2023

In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorith... more In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorithm for the reconstruction of missing samples. The proposed IF estimation and sparse reconstruction algorithm is developed by adding a refinement step where the crude estimates of IFs and signal components are further improved through the reestimation stage. During the re-estimation stage, both IFs, as well as the signal components, are re-estimated by removing all the remaining components. Experimental results indicate that the proposed strategy improves both the accuracy of IF estimates as well as missing samples.

Research Square (Research Square), Dec 20, 2022

In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorith... more In this study, we propose an instantaneous frequency (IF) estimation and then apply this algorithm for the reconstruction of missing samples. The proposed IF estimation and sparse reconstruction algorithm is developed by adding a refinement step where the crude estimates of IFs and signal components are further improved through the reestimation stage. During the re-estimation stage, both IFs, as well as the signal components, are re-estimated by removing all the remaining components. Experimental results indicate that the proposed strategy improves both the accuracy of IF estimates as well as missing samples.

Multidimensional Systems and Signal Processing, Feb 26, 2022

IEEE Signal Processing Letters, Feb 1, 2013

Circuits Systems and Signal Processing, Jan 5, 2023

Adaptive directional time-frequency distribution (ADTFD) is an efficient TFD, which has outperfor... more Adaptive directional time-frequency distribution (ADTFD) is an efficient TFD, which has outperformed most of the adaptive and fixed TFDs. The ADTFD locally optimizes the direction of the smoothing kernel on the basis of directional Gaussian or double derivative directional Gaussian filter (DGF). However, high computation cost of ADTFD has made this method inconvenient for processing real-life signals, i.e, biomedical signals. This paper addresses this problem and introduces a low-cost ADTFD with much lower computation cost and approximately similar efficiency of ADTFD. In the proposed method, instead of iterative filtering in different directions, which is computationally expensive, the optimized directions are estimated using the Radon transform of the modulus of the signal's ambiguity function. The results show that the proposed method is much faster than the ADTFD.

Sensors, Apr 15, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Circuits, Systems, and Signal Processing

2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI), 2017

Spikes are one of the main characteristics of a seizure electroencephalogram (EEG) signal. This f... more Spikes are one of the main characteristics of a seizure electroencephalogram (EEG) signal. This feature plays an important role in seizure abnormality detection in EEG signals. The objective of this work is to provide a methodology to enhance this characteristic in the time-frequency domain. To achieve this goal first, we amplify the spike components in the raw EEG signal using the differential window, then a modified version of adaptive directional time-frequency distribution of the amplified signal is computed. The performance of the proposed method assessed using a simulated and a real EEG data. The results show an improvement in the time-frequency representations of a signal with spikes components. Different TFDs are tested, the modified-ADTFD provides the best performance among the selected TFDs.

Signal, Image and Video Processing, 2021

This paper presents a computational efficient method to estimate the IF of multi-component signal... more This paper presents a computational efficient method to estimate the IF of multi-component signals for both mono-sensor and multi-sensor recordings. The algorithm uses fractional Fourier windows to find out both the highest energy TF point and the optimal rotation order of the analysis window at that point. The detected peak and rotation order are then used to track the IF curve by using linear interpolation to skip a predetermined number of samples, thus reducing the computational cost. The estimated IF is then used to remove the strongest component from the mixture, and this process is repeated till IFs of all the components are estimated. Experimental results indicate that the proposed method achieves similar performance in terms of the accuracy of IF estimate as that of the state-of-the-art method while significantly reducing the computational cost.

Social Science Research Network, 2022

Signal Processing, May 1, 2023

Signal, Image and Video Processing