Pub Date : 2024-09-06DOI: 10.1007/s00034-024-02827-7
Wentao Zhang, Chen Miao, Mengjie Jiang, Wen Wu
Accurately estimating the direction of arrival (DOA) of wideband signals with a sensor array is critical in communications, radar, and the Internet of Things. This paper proposes two single-source DOA estimation methods for wideband linear frequency modulation signals: time-delay mixing multiple signal classification (TDM-MUSIC) and enhanced self-mixing MUSIC (ESM-MUSIC). TDM-MUSIC employs time-delay mixing of the received signal to construct an equivalent single-frequency signal model, thereby enhancing estimation accuracy while maintaining reasonable computational efficiency. ESM-MUSIC improves the conventional self-mixing model by adding frequency correction steps, resulting in excellent DOA estimation performance at the expense of computational complexity. Unlike conventional methods that rely on approximate models, our methods establish more accurate equivalent models. A key advantage of our methods is that they allow flexible adjustment of the optimal sensor inter-element spacing in arrays based on the equivalent signal model rather than the actual signal model, simplifying engineering fabrication and reducing mutual coupling between sensors. The paper establishes the Cramér–Rao bounds for both proposed methods and demonstrates their superiority over existing methods through comprehensive numerical simulations. Further, the experiment using a TI-AWR2243 multi-sensor array radar system confirms that our methods are feasible for practical engineering applications.
在通信、雷达和物联网领域,利用传感器阵列准确估计宽带信号的到达方向(DOA)至关重要。本文针对宽带线性频率调制信号提出了两种单源 DOA 估算方法:时延混合多信号分类法(TDM-MUSIC)和增强型自混合 MUSIC 法(ESM-MUSIC)。TDM-MUSIC 利用接收信号的时延混合来构建等效的单频信号模型,从而在保持合理计算效率的同时提高估计精度。ESM-MUSIC 通过增加频率校正步骤来改进传统的自混频模型,从而在降低计算复杂度的同时获得出色的 DOA 估计性能。与依赖近似模型的传统方法不同,我们的方法建立了更精确的等效模型。我们的方法的一个主要优势是可以根据等效信号模型而非实际信号模型灵活调整阵列中传感器的最佳元件间距,从而简化工程制造并减少传感器之间的相互耦合。论文通过全面的数值模拟,确定了两种拟议方法的 Cramér-Rao 边界,并证明了它们优于现有方法。此外,使用 TI-AWR2243 多传感器阵列雷达系统进行的实验证实,我们的方法在实际工程应用中是可行的。
{"title":"Single-Source DOA Estimation for Wideband LFM Signal: Time-Delay Mixing and Enhanced Self-Mixing MUSIC Methods","authors":"Wentao Zhang, Chen Miao, Mengjie Jiang, Wen Wu","doi":"10.1007/s00034-024-02827-7","DOIUrl":"https://doi.org/10.1007/s00034-024-02827-7","url":null,"abstract":"<p>Accurately estimating the direction of arrival (DOA) of wideband signals with a sensor array is critical in communications, radar, and the Internet of Things. This paper proposes two single-source DOA estimation methods for wideband linear frequency modulation signals: time-delay mixing multiple signal classification (TDM-MUSIC) and enhanced self-mixing MUSIC (ESM-MUSIC). TDM-MUSIC employs time-delay mixing of the received signal to construct an equivalent single-frequency signal model, thereby enhancing estimation accuracy while maintaining reasonable computational efficiency. ESM-MUSIC improves the conventional self-mixing model by adding frequency correction steps, resulting in excellent DOA estimation performance at the expense of computational complexity. Unlike conventional methods that rely on approximate models, our methods establish more accurate equivalent models. A key advantage of our methods is that they allow flexible adjustment of the optimal sensor inter-element spacing in arrays based on the equivalent signal model rather than the actual signal model, simplifying engineering fabrication and reducing mutual coupling between sensors. The paper establishes the Cramér–Rao bounds for both proposed methods and demonstrates their superiority over existing methods through comprehensive numerical simulations. Further, the experiment using a TI-AWR2243 multi-sensor array radar system confirms that our methods are feasible for practical engineering applications.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"13 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1007/s00034-024-02847-3
Heping Shi, Xinyu Weng, Guanghui Yan, Shaohua Wang
This letter proposes a two-dimensional direction-of-arrival (2-D DOA) estimation method for conjugate augmented spatial-temporal L-shaped arrays based on the rank-reduction principle. The basic idea of the proposed method is to utilize the spatial-temporal 2-D structure of the data received by the array and the conjugate symmetry of the signal delay auto-correlation function to construct a conjugate augmented spatial-temporal cross-correlation matrix. Then, the properties of the matrix Kronecker product can be utilized to decouple the steering vector of the 2-D angle of arrival and utilize the rank-reduction and one-dimensional spectral peak search to automatically pair the 2-D DOA. The proposed method can handle the 2-D angle-estimation problem under underdetermined cases, and the effectiveness of the proposed method was verified by computer simulations.
本文提出了一种基于秩还原原理的共轭增强时空 L 型阵列二维到达方向(2-DOA)估计方法。该方法的基本思想是利用阵列接收数据的时空二维结构和信号延迟自相关函数的共轭对称性来构建共轭增强时空交叉相关矩阵。然后,利用矩阵 Kronecker 积的特性来解耦二维到达角的转向矢量,并利用秩还原和一维谱峰搜索来自动配对二维 DOA。所提出的方法可以处理欠定情况下的二维角度估计问题,并通过计算机仿真验证了所提出方法的有效性。
{"title":"Spatial-Temporal 2-D DOA Estimation Based on Rank-Reduction","authors":"Heping Shi, Xinyu Weng, Guanghui Yan, Shaohua Wang","doi":"10.1007/s00034-024-02847-3","DOIUrl":"https://doi.org/10.1007/s00034-024-02847-3","url":null,"abstract":"<p>This letter proposes a two-dimensional direction-of-arrival (2-D DOA) estimation method for conjugate augmented spatial-temporal L-shaped arrays based on the rank-reduction principle. The basic idea of the proposed method is to utilize the spatial-temporal 2-D structure of the data received by the array and the conjugate symmetry of the signal delay auto-correlation function to construct a conjugate augmented spatial-temporal cross-correlation matrix. Then, the properties of the matrix Kronecker product can be utilized to decouple the steering vector of the 2-D angle of arrival and utilize the rank-reduction and one-dimensional spectral peak search to automatically pair the 2-D DOA. The proposed method can handle the 2-D angle-estimation problem under underdetermined cases, and the effectiveness of the proposed method was verified by computer simulations.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"94 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1007/s00034-024-02845-5
S. Karthikeyani, S. Sasipriya, M. Ramkumar
Classification of cardiac diseases from electrocardiogram signals is essential for enhancing patient results to minimize healthcare costs, early detection and accurate diagnosis. This research investigates the integration of dimensionality reduction methods with various deep learning classifiers to improve the accuracy and efficient classification of cardiac disease. Uniform Manifold Approximation and Projection combined with Principal Component Analysis is used for dimensionality reduction, that captures both global and local data structures. Deep learning classifiers with convolutional neural networks, capsule networks, recurrent neural networks, graph neural networks, deep long short-term memory and automatical attention-based convolutional neural networks are employed for classification. The Adaptive spiral Flying Sparrow Search algorithm optimizes classifier parameters for enhance accuracy. Performance is evaluated through various metrics, with area under the receiver operating characteristic curve, accuracy, F1-Score, precision and recall. The proposed method's outcomes are compared with and without optimization to demonstrate the efficiency and attains 92.16%, 96.15%, 91.95%, 94.65%, 91.45% and 92.85% accuracy respectively for each classification method.
{"title":"An Evaluation of Dimensionality Reduction and Classification Techniques for Cardiac Disease Diagnosis from ECG Signals with Various Deep Learning Classifiers","authors":"S. Karthikeyani, S. Sasipriya, M. Ramkumar","doi":"10.1007/s00034-024-02845-5","DOIUrl":"https://doi.org/10.1007/s00034-024-02845-5","url":null,"abstract":"<p>Classification of cardiac diseases from electrocardiogram signals is essential for enhancing patient results to minimize healthcare costs, early detection and accurate diagnosis. This research investigates the integration of dimensionality reduction methods with various deep learning classifiers to improve the accuracy and efficient classification of cardiac disease. Uniform Manifold Approximation and Projection combined with Principal Component Analysis is used for dimensionality reduction, that captures both global and local data structures. Deep learning classifiers with convolutional neural networks, capsule networks, recurrent neural networks, graph neural networks, deep long short-term memory and automatical attention-based convolutional neural networks are employed for classification. The Adaptive spiral Flying Sparrow Search algorithm optimizes classifier parameters for enhance accuracy. Performance is evaluated through various metrics, with area under the receiver operating characteristic curve, accuracy, F1-Score, precision and recall. The proposed method's outcomes are compared with and without optimization to demonstrate the efficiency and attains 92.16%, 96.15%, 91.95%, 94.65%, 91.45% and 92.85% accuracy respectively for each classification method.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"6 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1007/s00034-024-02849-1
Amir Alizadeh, Saeid Pakravan, Ghosheh Abed Hodtani
Phase noise (PN) is a prevalent challenge in oscillator-driven systems, leading to spectral dispersion of the power spectral density (PSD) around a Dirac delta function. This paper addresses the task of estimating a communication channel affected by additive white Gaussian noise (AWGN) and phase noise. Traditional estimation methods such as the least mean square (LMS) and mean square error (MSE) criteria are deemed inadequate due to the unique characteristics of phase noise. In this study, we propose a novel approach for PN channel estimation utilizing information-theoretic learning (ITL) principles, specifically focusing on the maximum correntropy criterion (MCC). By employing MCC, our method enhances the robustness of the channel estimator in steady-state conditions, thereby improving the accuracy of parameter estimation. Additionally, to expedite the convergence rate of our algorithm, we introduce a novel mixed-LMS approach that amalgamates elements of both MSE and MCC. This hybrid technique leverages the strengths of each criterion, resulting in a more efficient and accurate estimation of the PN-affected channel. Through comprehensive analysis and experimentation, our proposed method demonstrates its effectiveness in mitigating the impact of phase noise on channel estimation.
{"title":"Channel Parameter Estimation in the Presence of Phase Noise Based on Maximum Correntropy Criterion","authors":"Amir Alizadeh, Saeid Pakravan, Ghosheh Abed Hodtani","doi":"10.1007/s00034-024-02849-1","DOIUrl":"https://doi.org/10.1007/s00034-024-02849-1","url":null,"abstract":"<p>Phase noise (PN) is a prevalent challenge in oscillator-driven systems, leading to spectral dispersion of the power spectral density (PSD) around a Dirac delta function. This paper addresses the task of estimating a communication channel affected by additive white Gaussian noise (AWGN) and phase noise. Traditional estimation methods such as the least mean square (LMS) and mean square error (MSE) criteria are deemed inadequate due to the unique characteristics of phase noise. In this study, we propose a novel approach for PN channel estimation utilizing information-theoretic learning (ITL) principles, specifically focusing on the maximum correntropy criterion (MCC). By employing MCC, our method enhances the robustness of the channel estimator in steady-state conditions, thereby improving the accuracy of parameter estimation. Additionally, to expedite the convergence rate of our algorithm, we introduce a novel mixed-LMS approach that amalgamates elements of both MSE and MCC. This hybrid technique leverages the strengths of each criterion, resulting in a more efficient and accurate estimation of the PN-affected channel. Through comprehensive analysis and experimentation, our proposed method demonstrates its effectiveness in mitigating the impact of phase noise on channel estimation.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"21 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-03DOI: 10.1007/s00034-024-02829-5
Lin Luo, Yi Yu, Tao Yang, Ke Li, Hongsen He
The projection order of the affine projection algorithm (APA) affects not only the convergence performance but also the steady-state behavior. Therefore, for solving the fixed projection order of the conventional APA, we develop a new scheme of variable projection order (VPO) that enables the evolution from the maximum projection order to the minimum one by resorting to the adaptation of the mixing factor, thereby yielding a novel APA with VPO. Moreover, for dealing with sparse systems with fast convergence, we extend the proposed VPO scheme to proportionate APA and develop a VPO-based memory proportionate APA. Simulation results in the scenarios of system identification and acoustic echo cancellation have shown that the proposed algorithms have a faster convergence rate and lower steady-state error as compared to their original counterparts and the existing VPO algorithms.
{"title":"Affine Projection Algorithms with Novel Schemes of Variable Projection Order","authors":"Lin Luo, Yi Yu, Tao Yang, Ke Li, Hongsen He","doi":"10.1007/s00034-024-02829-5","DOIUrl":"https://doi.org/10.1007/s00034-024-02829-5","url":null,"abstract":"<p>The projection order of the affine projection algorithm (APA) affects not only the convergence performance but also the steady-state behavior. Therefore, for solving the fixed projection order of the conventional APA, we develop a new scheme of variable projection order (VPO) that enables the evolution from the maximum projection order to the minimum one by resorting to the adaptation of the mixing factor, thereby yielding a novel APA with VPO. Moreover, for dealing with sparse systems with fast convergence, we extend the proposed VPO scheme to proportionate APA and develop a VPO-based memory proportionate APA. Simulation results in the scenarios of system identification and acoustic echo cancellation have shown that the proposed algorithms have a faster convergence rate and lower steady-state error as compared to their original counterparts and the existing VPO algorithms.\u0000</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"10 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1007/s00034-024-02838-4
Sihan Yuan, Gengxin Ning, Yushen Lin
The underwater environment introduces uncertainty into the acoustic velocity, which affects the performance of traditional direction of arrival (DOA) estimation methods. This research proposes a cascaded neural network based underwater DOA estimate approach to address this issue. In this method, the cascade neural network is composed of a velocity regressor and a velocity classifier. To determine the estimated value of acoustic velocity, the velocity classifier first breaks down the input data into distinct velocity domains. It then regulates the velocity regression process. Then, the array steering matrix predicted by the blind source separation algorithm is utilized to determine the angle, and the acoustic velocity is modiffed by the cascaded neural network. Eventually, it is possible to derive the DOA estimation value under the calculated acoustic velocity. The suggested method has a high estimation accuracy especially when the acousitc velocity is unknown, as shown by the simulation results.
水下环境会给声速带来不确定性,从而影响传统的到达方向(DOA)估计方法的性能。针对这一问题,本研究提出了一种基于级联神经网络的水下 DOA 估计方法。在该方法中,级联神经网络由速度回归器和速度分类器组成。为了确定声速的估计值,速度分类器首先将输入数据分解成不同的速度域。然后,它对速度回归过程进行调节。然后,利用盲源分离算法预测的阵列转向矩阵来确定角度,并通过级联神经网络对声速进行调制。最终,可以在计算出的声速下得出 DOA 估计值。模拟结果表明,所建议的方法具有很高的估计精度,尤其是在声速未知的情况下。
{"title":"An Underwater Velocity-Independent DOA Estimation Method Based on Cascaded Neural Network","authors":"Sihan Yuan, Gengxin Ning, Yushen Lin","doi":"10.1007/s00034-024-02838-4","DOIUrl":"https://doi.org/10.1007/s00034-024-02838-4","url":null,"abstract":"<p>The underwater environment introduces uncertainty into the acoustic velocity, which affects the performance of traditional direction of arrival (DOA) estimation methods. This research proposes a cascaded neural network based underwater DOA estimate approach to address this issue. In this method, the cascade neural network is composed of a velocity regressor and a velocity classifier. To determine the estimated value of acoustic velocity, the velocity classifier first breaks down the input data into distinct velocity domains. It then regulates the velocity regression process. Then, the array steering matrix predicted by the blind source separation algorithm is utilized to determine the angle, and the acoustic velocity is modiffed by the cascaded neural network. Eventually, it is possible to derive the DOA estimation value under the calculated acoustic velocity. The suggested method has a high estimation accuracy especially when the acousitc velocity is unknown, as shown by the simulation results.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"58 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1007/s00034-024-02834-8
Armin Mohammadjany, Ali Reza Hazeri, Hossein Miar-Naimi
In this article, two accurate nonlinear methods are proposed to calculate non-symmetrical locking ranges of the Injected Cross-Coupled Oscillator (ICCO) with the parallel RLC tank and series RL with a parallel C tank for both weak and strong injection levels. By writing governing differential equations of circuit elements of the ICCO, graphical presenting of current vectors, and using the averaging method for solving nonlinear equations, equations of the ICCO are simplified. Then, exact non-symmetrical locking ranges are calculated using the iterative method. Moreover, the describing function of the oscillator’s nonlinear part, an inverse tangent function, is applied to the model. The inverse tangent function generates complicated governing differential equations of circuit elements that are accurate. Then, it is solved to ICCO for the first time and has novel results for calculating non-symmetrical locking ranges. There is a good agreement between theoretical and simulation results. The proposed non-symmetrical locking ranges are accurate in both weak and strong injections. The absolute percent of errors for various levels of the injection signal is less than 20%. In the bargain, proposed locking ranges are the most accurate compared to previously published results.
{"title":"Nonlinear Analyses of Unsymmetrical Locking Range of Injected Cross-Coupled Oscillator","authors":"Armin Mohammadjany, Ali Reza Hazeri, Hossein Miar-Naimi","doi":"10.1007/s00034-024-02834-8","DOIUrl":"https://doi.org/10.1007/s00034-024-02834-8","url":null,"abstract":"<p>In this article, two accurate nonlinear methods are proposed to calculate non-symmetrical locking ranges of the Injected Cross-Coupled Oscillator (ICCO) with the parallel RLC tank and series RL with a parallel C tank for both weak and strong injection levels. By writing governing differential equations of circuit elements of the ICCO, graphical presenting of current vectors, and using the averaging method for solving nonlinear equations, equations of the ICCO are simplified. Then, exact non-symmetrical locking ranges are calculated using the iterative method. Moreover, the describing function of the oscillator’s nonlinear part, an inverse tangent function, is applied to the model. The inverse tangent function generates complicated governing differential equations of circuit elements that are accurate. Then, it is solved to ICCO for the first time and has novel results for calculating non-symmetrical locking ranges. There is a good agreement between theoretical and simulation results. The proposed non-symmetrical locking ranges are accurate in both weak and strong injections. The absolute percent of errors for various levels of the injection signal is less than 20%. In the bargain, proposed locking ranges are the most accurate compared to previously published results.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"20 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1007/s00034-024-02840-w
Trapti Sharma, Deepa Sharma
The advancement of emerging technologies favors the proliferation of multi-valued logic design as it offers enhancement of circuit performance parameters with increased level of integration. This work has presented carbon nanotube field effect transistor (CNTFET) based ternary shift register designs which are realized by employing single-edge triggered ternary D-flip-flop cells with reset input. The dependency of threshold voltage on carbon nanotube physical dimensions is used for the realization of multiple threshold voltages in ternary logic designs. The D-flip flop design with reset capability implementation is performed using multiplexer based positive and negative latches arranged in master–slave architecture. Further, the D-flip-flop cells with reset input are combined to construct Ternary logic serial input serial output (SISO), parallel input parallel output (PIPO) and parallel input serial output (PISO) registers. The latching of the input across the output happens only if the reset input is high otherwise no latching is performed. The PISO register is operating in two modes of loading and shifting realized using NAND logic. The proposed ternary shift register designs using CNTFETs are simulated using HSPICE considering the 32 nm Stanford CNTFET model. The results demonstrate that for 4-bit register design, power and PDP improvements of more than 70% are achieved for SISO designs and a maximum of 90% is attained for PIPO and PISO register designs as compared to recent counterparts. The Monte-Carlo simulation results indicate robust and stable operation of the proposed designs when subjected to process variations.
{"title":"Efficient Design Approaches to Model Ternary D-Flip-Flop and Shift Registers in CNT Technology","authors":"Trapti Sharma, Deepa Sharma","doi":"10.1007/s00034-024-02840-w","DOIUrl":"https://doi.org/10.1007/s00034-024-02840-w","url":null,"abstract":"<p>The advancement of emerging technologies favors the proliferation of multi-valued logic design as it offers enhancement of circuit performance parameters with increased level of integration. This work has presented carbon nanotube field effect transistor (CNTFET) based ternary shift register designs which are realized by employing single-edge triggered ternary D-flip-flop cells with reset input. The dependency of threshold voltage on carbon nanotube physical dimensions is used for the realization of multiple threshold voltages in ternary logic designs. The D-flip flop design with reset capability implementation is performed using multiplexer based positive and negative latches arranged in master–slave architecture. Further, the D-flip-flop cells with reset input are combined to construct Ternary logic serial input serial output (SISO), parallel input parallel output (PIPO) and parallel input serial output (PISO) registers. The latching of the input across the output happens only if the reset input is high otherwise no latching is performed. The PISO register is operating in two modes of loading and shifting realized using NAND logic. The proposed ternary shift register designs using CNTFETs are simulated using HSPICE considering the 32 nm Stanford CNTFET model. The results demonstrate that for 4-bit register design, power and PDP improvements of more than 70% are achieved for SISO designs and a maximum of 90% is attained for PIPO and PISO register designs as compared to recent counterparts. The Monte-Carlo simulation results indicate robust and stable operation of the proposed designs when subjected to process variations.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"46 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1007/s00034-024-02841-9
Haiquan Zhao, Zian Cao, Yida Chen
In order to solve the problem of deteriorating performance of the conventional subband adaptive filtering algorithm when processing the EIV model with impulsive noise, this paper proposes the robust Total Least Mean M-Estimate normalized subband filter (TLMM-NSAF) adaptive algorithm based on the M-estimation function. In addition, we conduct a detailed theoretical performance analysis of the TLMM-NSAF algorithm, which allows us to determine the stable step size range and theoretical steady-state mean squared deviation of the algorithm. To further improve the algorithm's performance, we propose a new variable step size method. Finally, we compared the algorithm with other competition algorithms in applications of system identification and acoustic echo cancellation. Simulation results have demonstrated the superiority of our proposed algorithm, as well as the consistency between the theoretical values and the simulated values.
为了解决传统子带自适应滤波算法在处理具有脉冲噪声的 EIV 模型时性能下降的问题,本文提出了基于 M 估计函数的鲁棒总最小均值归一化子带滤波器(TLMM-NSAF)自适应算法。此外,我们还对 TLMM-NSAF 算法进行了详细的理论性能分析,从而确定了算法的稳定步长范围和理论稳态均方偏差。为了进一步提高算法性能,我们提出了一种新的可变步长方法。最后,我们将该算法与其他竞争算法在系统识别和声学回声消除应用中进行了比较。仿真结果证明了我们提出的算法的优越性,以及理论值与仿真值之间的一致性。
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Pub Date : 2024-08-27DOI: 10.1007/s00034-024-02825-9
Bala Bhaskar Duddeti
The mathematical modeling of the real-time system results in large-dimensional ordinary or partial differential equations, which are challenging to employ for investigation and control synthesis. Finding a comparable system of the same kind in a lower-order dimension that can maintain the core characteristics of the higher-order system (HOS) is essential. This article discusses a novel technique for HOS’s reduced order approximation and control design. The proposed method modifies the Schur method for balanced truncation. The method circumvents the requirement of balancing transformation and steady-state gain (SSG) deviation as required in the truncated model reduction algorithm. The offered technique eliminates the SSG deviation without altering the dynamical behavior compared to the HOS by appending a gain enhancement factor to the numerator polynomial of the reduced system transfer matrix. The offered technique ensures that the reduced system retains the HOS stability, passivity, SSG, and all critical characteristics. The recommended method’s findings are compared to the outcomes of recently published work’s lower-order models. Further, using the proposed method, the reduced model has been used to design a PID controller for the flexible-missile control model and an automatic voltage regulator system. The controller produced using the simplified model provides almost the exact time domain specifications (TDS) as the controller made using the HOS, and its design is also relatively more straightforward. Step response and TDS assess lower- and higher-order controller performance.
实时系统的数学建模会产生大维度的常微分方程或偏微分方程,这对研究和控制合成是一个挑战。在低阶维度上找到一个能保持高阶系统(HOS)核心特性的同类可比系统至关重要。本文讨论了一种用于高阶系统低阶近似和控制设计的新技术。所提出的方法修改了用于平衡截断的舒尔方法。该方法规避了截断模型缩减算法中平衡变换和稳态增益(SSG)偏差的要求。与 HOS 相比,所提供的技术通过在还原系统传递矩阵的分子多项式中附加增益增强因子,消除了 SSG 偏差,同时不改变动力学行为。所提供的技术可确保简化系统保持 HOS 的稳定性、被动性、SSG 和所有关键特性。建议方法的结果与最近发表的低阶模型结果进行了比较。此外,利用建议的方法,简化模型已被用于为柔性导弹控制模型和自动电压调节器系统设计 PID 控制器。使用简化模型制作的控制器与使用 HOS 制作的控制器具有几乎完全相同的时域规格(TDS),而且其设计也相对更加简单。阶跃响应和 TDS 评估了低阶和高阶控制器的性能。
{"title":"Model Order Reduction Strategy for LTI Systems and Application to PID Controller Design","authors":"Bala Bhaskar Duddeti","doi":"10.1007/s00034-024-02825-9","DOIUrl":"https://doi.org/10.1007/s00034-024-02825-9","url":null,"abstract":"<p>The mathematical modeling of the real-time system results in large-dimensional ordinary or partial differential equations, which are challenging to employ for investigation and control synthesis. Finding a comparable system of the same kind in a lower-order dimension that can maintain the core characteristics of the higher-order system (HOS) is essential. This article discusses a novel technique for HOS’s reduced order approximation and control design. The proposed method modifies the Schur method for balanced truncation. The method circumvents the requirement of balancing transformation and steady-state gain (SSG) deviation as required in the truncated model reduction algorithm. The offered technique eliminates the SSG deviation without altering the dynamical behavior compared to the HOS by appending a gain enhancement factor to the numerator polynomial of the reduced system transfer matrix. The offered technique ensures that the reduced system retains the HOS stability, passivity, SSG, and all critical characteristics. The recommended method’s findings are compared to the outcomes of recently published work’s lower-order models. Further, using the proposed method, the reduced model has been used to design a PID controller for the flexible-missile control model and an automatic voltage regulator system. The controller produced using the simplified model provides almost the exact time domain specifications (TDS) as the controller made using the HOS, and its design is also relatively more straightforward. Step response and TDS assess lower- and higher-order controller performance.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"284 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}