{"title":"Inverse-Free Hybrid Spatial-Temporal Derivative Neural Network for Time-Varying Matrix Moore–Penrose Inverse and Its Circuit Schematic","authors":"Bing Zhang;Yuhua Zheng;Shuai Li;Xinglong Chen;Yao Mao;Duc Truong Pham","doi":"10.1109/TCSII.2025.3530639","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3530639","url":null,"abstract":"This brief introduces the Inverse-free hybrid spatial-temporal derivative neural network (IHSTDNN), a novel neural network that integrates principles from gradient neural networks (GNN) and zeroing neural networks (ZNN) to address the time-varying matrix Moore-Penrose inverse. The IHSTDNN features an explicit dynamic structure, eliminating the need for inverse operations. The design of its circuit is outlined, and the model’s convergence and robustness are examined theoretically. Numerical simulations and experimental data demonstrate that the IHSTDNN outperforms other existing models, achieving a faster convergence rate and reduced steady-state error.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"499-503"},"PeriodicalIF":4.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guanyu Chen;Mingju Chen;Tengxiao Wang;Haibing Wang;Xiang Fu;Yingcheng Lin;Liyuan Liu;Cong Shi
{"title":"An Edge Neuromorphic Processor With High-Accuracy On-Chip Aggregate-Label Learning","authors":"Guanyu Chen;Mingju Chen;Tengxiao Wang;Haibing Wang;Xiang Fu;Yingcheng Lin;Liyuan Liu;Cong Shi","doi":"10.1109/TCSII.2025.3529670","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3529670","url":null,"abstract":"Neuromorphic computing with bio-inspired spiking neural networks (SNNs) offers an energy-efficient paradigm for edge intelligence. But, achieving practically high on-chip SNN learning accuracy with limited hardware resources still remains challenging. To tackle this issue, this brief proposes an edge neuromorphic processor architecture enabling computationally-simple optimized aggregate-label (AL) algorithm to realize high-accuracy on-chip learning. To maximize utilization of multicore resources and minimize processing latency, our processor adopts techniques including uniform neuron-core mapping, layer-alternating workflow, time-step pipeline and event-driven scheme. We benchmarked our processor on an FPGA device, and attained high on-chip learning accuracies of 97.21%, 88.1%, 90.92%, 100% and 99.22% on MNIST, Fashion-MNIST, ETH-80, ORL-10, and Yale-10 datasets, respectively, using a small 2-layer fully-connected (FC) SNN, with a moderate resource cost and a relatively high energy efficiency. These results indicate that our design is very useful for many self-adaptive edge systems.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"509-513"},"PeriodicalIF":4.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predefined-Time Command Filtered Control for Tracking and Synchronization of Multi-Motor Servo Systems With Fuzzy Approximator","authors":"Xiang Wang;Baofang Wang;Jinpeng Yu","doi":"10.1109/TCSII.2025.3529750","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3529750","url":null,"abstract":"This brief proposes a predefined-time command filtered control strategy for multi-motor servo systems to facilitate high-performance tracking and synchronization. For load tracking, a predefined-time control approach is integrated within the backstepping framework, which accelerates the convergence rate and simplifies the adjustment of the convergence time. Command filters are utilized to obtain the derivatives of virtual control signals, and a compensation mechanism is developed to reduce filtering errors. Furthermore, a fuzzy logic system is constructed to estimate and counteract the frictional effect. For motor synchronization, a practical grouping control approach is designed for four motors, with control inputs overlaid on command signals of motor currents to rapidly realize synchronization of motor speeds. The predefined-time stability of the closed-loop system is demonstrated. The practicality and effectiveness of the proposed strategy are validated by experimental results.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"494-498"},"PeriodicalIF":4.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Hardware-Friendly Shuffling Countermeasure Against Side-Channel Attacks for Kyber","authors":"Dejun Xu;Kai Wang;Jing Tian","doi":"10.1109/TCSII.2025.3528751","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3528751","url":null,"abstract":"CRYSTALS-Kyber has been standardized as the only key-encapsulation mechanism (KEM) scheme by NIST to withstand attacks by large-scale quantum computers. However, the side-channel attacks (SCAs) on its implementation are still needed to be well considered for the upcoming migration. In this brief, we propose a secure and efficient hardware implementation for Kyber by incorporating a novel compact shuffling architecture. First of all, we modify the Fisher-Yates shuffle to make it more hardware-friendly. We then design an optimized shuffling architecture for the well-known open-source Kyber hardware implementation to enhance the security of all known and potential side-channel leakage points. Finally, we implement the modified Kyber design on FPGA and evaluate its security and performance. The security is verified by conducting correlation power analysis (CPA) and test vector leakage assessment (TVLA) on the hardware. Meanwhile, FPGA place-and-route results show that the proposed design reports only 8.7% degradation on the hardware efficiency compared with the original unprotected version, much better than existing hardware hiding schemes.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"504-508"},"PeriodicalIF":4.0,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenjie Mei;Xiaorui Wang;Yanrong Lu;Ke Yu;Shihua Li
{"title":"Learning and Current Prediction of PMSM Drive via Differential Neural Networks","authors":"Wenjie Mei;Xiaorui Wang;Yanrong Lu;Ke Yu;Shihua Li","doi":"10.1109/TCSII.2025.3527024","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3527024","url":null,"abstract":"Learning models for dynamical systems in continuous time is significant for understanding complex phenomena and making accurate predictions. This brief presents a novel approach utilizing differential neural networks (DNNs) to model nonlinear systems, specifically permanent magnet synchronous motors (PMSMs), and to predict their current trajectories. The efficacy of our approach is validated through experiments conducted under various load disturbances and no-load conditions. The results demonstrate that our method effectively and accurately reconstructs the original systems, showcasing strong short-term and long-term prediction capabilities and robustness. This brief provides valuable insights into learning the inherent dynamics of complex dynamical data and holds potential for further applications in fields such as weather forecasting, robotics, and collective behavior analysis.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"489-493"},"PeriodicalIF":4.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Effect of Memory Error in a Time-Interleaved Pipeline ADC With a Shared Residue Amplifier","authors":"Debajit Basak;Siji Huang;George Yuan","doi":"10.1109/TCSII.2025.3526875","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3526875","url":null,"abstract":"Compared to traditional time-interleaved (TI) pipeline ADC, shared residue amplifier (RA) architecture is potentially more power efficient and requires simpler calibration. However, the shared RA architecture suffers from memory error, which severely degrades its linearity. Typically, a reset phase is needed at the RA’s input to avoid this memory error. The reset phase is particularly problematic for high-speed ADCs as it shortens the amplification time, leading to higher power consumption in the RA. This brief analyzes the effect of memory error and presents a simple digital memory correction technique for a reset-free and shared open-loop based pipeline ADC. A 14-bit TI pipeline-SAR ADC, running at 2 GS/s, is designed and fabricated to verify the proposed analysis and correction method. Experimental results show improvements of upto 5.1 dB in the signal-to-noise-and-distortion ratio (SNDR) and more than two times in the integral nonlinearity (INL) with the proposed digital memory correction technique.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"434-438"},"PeriodicalIF":4.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis and Design of a Type-II Reference-Sampling PLL Using Gain-Boosting Phase Detector With Sampling Capacitor Reduction","authors":"Tailong Xu;Haoran Li;Xi Meng;Xiangxun Zhan;Yatao Peng;Jun Yin;Shiheng Yang;Chao Fan;Zhixiang Huang;Rui P. Martins;Pui-In Mak","doi":"10.1109/TCSII.2025.3526921","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3526921","url":null,"abstract":"This brief analyzes the phase noise (PN) and reference (REF) spur performance of the reference-sampling (RS) PLL when the total sampling capacitor <inline-formula> <tex-math>$(C_{mathrm { S}})$ </tex-math></inline-formula> is reduced to save the power consumption of the crystal oscillator (XO) buffer. Based on the analysis, the saved power consumption from the XO buffer can be utilized to improve the PN of the voltage-controlled oscillator (VCO), which compensates for the in-band PN degradation induced by the <inline-formula> <tex-math>$C_{mathrm { S}}$ </tex-math></inline-formula> reduction. Based on this theme, we can reduce the total power consumption of the RS-PLL and the XO buffer without degrading the output root-mean-square (RMS) jitter by reducing <inline-formula> <tex-math>$C_{mathrm { S}}$ </tex-math></inline-formula> if a VCO with a high figure-of-merit (FoM) and a low <inline-formula> <tex-math>$1/{f}^{3}$ </tex-math></inline-formula> PN corner frequency is available. A type-II RS-PLL prototype utilizing a gain-boosting RS phase detector to suppress the voltage-to-current <inline-formula> <tex-math>$(G_{mathrm { M}})$ </tex-math></inline-formula> circuit noise is designed to verify the presented design strategy. With the aid of an inverse-class-F VCO with a FoM of 190.4 dBc/Hz at 1 MHz offset frequency and a <inline-formula> <tex-math>$1/{f}^{3}$ </tex-math></inline-formula> PN corner frequency of 300 kHz across the frequency tuning range from 5.2 GHz to 6.1 GHz, the RS-PLL prototype fabricated in a 65-nm CMOS achieves low RMS jitter and REF spur of 64.8 fs and -84.1 dBc, respectively, while dissipating 6.9 mW, corresponding to a jitter-power FoM (<inline-formula> <tex-math>$rm FoM{_{J}}$ </tex-math></inline-formula>) of -255.4 dB.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 3","pages":"439-443"},"PeriodicalIF":4.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"2024 Index IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 71","authors":"","doi":"10.1109/TCSII.2025.3527324","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3527324","url":null,"abstract":"","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"71 12","pages":"1-187"},"PeriodicalIF":4.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Safaa Abdelfattah;Hussein M. E. Hussein;Aatmesh Shrivastava;Marvin Onabajo
{"title":"Instrumentation Amplifier Input Impedance Calibration With Machine Learning-Based Optimizations","authors":"Safaa Abdelfattah;Hussein M. E. Hussein;Aatmesh Shrivastava;Marvin Onabajo","doi":"10.1109/TCSII.2025.3526145","DOIUrl":"https://doi.org/10.1109/TCSII.2025.3526145","url":null,"abstract":"This brief introduces a digital calibration technique to boost the input impedance of instrumentation amplifiers (IAs) with digitally tunable input impedance. The technique employs two machine learning-driven optimization algorithms, the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, to efficiently control integrated capacitor banks within the IA for the determination of the optimal input impedance. These algorithms offer a significant time reduction compared to a calibration with an exhaustive search, reducing calibration time by a factor of over <inline-formula> <tex-math>$10^{6}$ </tex-math></inline-formula> (with four 9-bit digital control words) while conserving computational resources. A prototype platform was developed to automatically optimize a fabricated IA test chip designed with 65-nm CMOS technology, which allows to test the machine learning algorithms using a microcontroller to control the digitally tunable input impedance. With an extra input capacitance of 100 pF, the GA algorithm achieved an input impedance of 1.75 G<inline-formula> <tex-math>$Omega $ </tex-math></inline-formula> after four generations (iterations), while the PSO algorithm achieved 1.27 G<inline-formula> <tex-math>$Omega $ </tex-math></inline-formula> with five iterations.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 2","pages":"394-398"},"PeriodicalIF":4.0,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Series-LC-Assisted Oscillator Achieving –140.2 dBc/Hz Phase Noise and 187.5 dBc/Hz FoM at 10 MHz Offset From 10.7 GHz","authors":"Xiangxun Zhan;Jun Yin;Rui P. Martins;Pui-In Mak","doi":"10.1109/TCSII.2024.3524556","DOIUrl":"https://doi.org/10.1109/TCSII.2024.3524556","url":null,"abstract":"This brief presents a series-LC-assisted oscillator. By utilizing the series LC, the tank impedance at the oscillation frequency is significantly reduced compared to the conventional parallel LC tank, which contributes to reducing the phase noise (PN). Additionally, large-size cross-coupled transistors should be utilized to maintain the oscillation due to the low tank impedance. This induces a large parasitic capacitance that limits the frequency tuning range (FTR) at high frequencies in the conventional cross-coupled oscillator. In contrast, the presented oscillator can operate above 10 GHz with a sufficient FTR, thanks to the capacitance-boosting capability of the series LC. Fabricated in a 65 nm CMOS process, the oscillator achieves a PN of −140.2 dBc/Hz at 10 MHz offset from a 10.7 GHz carrier, consuming a power consumption of 21 mW, resulting in a figure of merit (FoM) of 187.5 dBc/Hz.","PeriodicalId":13101,"journal":{"name":"IEEE Transactions on Circuits and Systems II: Express Briefs","volume":"72 2","pages":"389-393"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}