A simple on-chip automatic frequency tuning circuit is proposed. The tuning circuit is modified from voltage-controlled filter (VCF) frequency tuning circuit. We utilize an operational transconductance amplifier and a...A simple on-chip automatic frequency tuning circuit is proposed. The tuning circuit is modified from voltage-controlled filter (VCF) frequency tuning circuit. We utilize an operational transconductance amplifier and a capacitor to from a single-time constant (STC) circuit which can produce a controllable delay time clock to tune the frequency of the filter. It can efficiently reduce the deviations in the 3 dB bandwidth from the variations of PVT (Process, Voltage and Temperature). The design of the STC circuit is simpler than VCF and it has less chip area. The chip has been implanted using TCMC 0.35 μm CMOS technology and the power consumption is less than 9.05 mW.展开更多
A Gm-C complex filter with on-chip automatic tuning for wireless sensor networks is designed and implemented using 0.18 μm CMOS process. This filter is synthesized from a low-pass 5th-order Chebyshev RLC ladder filte...A Gm-C complex filter with on-chip automatic tuning for wireless sensor networks is designed and implemented using 0.18 μm CMOS process. This filter is synthesized from a low-pass 5th-order Chebyshev RLC ladder filter prototype by means of capacitors and fully balanced transconductors. A conventional phase-locked loop is used to realize the on-chip automatic tuning for both center frequency and bandwidth control. The filter is centered at 2 MHz with a bandwidth of 2.4 MHz. The measured results show that the filter provides more than 45 dB image rejection while the ripple in the pass-band is less than 1.2 dB. The complete filter including on-chip tuning circuit consumes 4.9 mA with 1.8 V single supply voltage.展开更多
A sixth-order Butterworth Gm-C low-pass filter（LPF） with a continuous tuning architecture has been implemented for a wireless LAN（WLAN） transceiver in 0.35μm CMOS technology.An interior node scaling technique has...A sixth-order Butterworth Gm-C low-pass filter（LPF） with a continuous tuning architecture has been implemented for a wireless LAN（WLAN） transceiver in 0.35μm CMOS technology.An interior node scaling technique has been applied directly to the LPF to improve the dynamic range and the structure of the LPF has been optimized to reduce both the die size and the current consumption.Measurement results show that the filter has 77.5 dB dynamic range,16.3 ns group delay variation,better than 3%cutoff frequency accuracy,and 0 dBm passband IIP3.The whole LPF with the tuning circuit dissipates only 1.42 mA（5 MHz cutoff frequency） or 2.81 mA（10 MHz cutoff frequency） from 2.85 V supply voltage,and only occupies 0.175 mm^2 die size.展开更多
This letter introduces a 4th order active RC complex filter with 1.SMHz center frequency and 1MHz bandwidth. The total harmonic distortion of the filter is less than -60dB and the image rejection ratio is greater than...This letter introduces a 4th order active RC complex filter with 1.SMHz center frequency and 1MHz bandwidth. The total harmonic distortion of the filter is less than -60dB and the image rejection ratio is greater than 60dB. A novel technique is also proposed in this letter to automatically adjust the variation of the time constant. The advantages of the proposed method are its high precision and simplicity. Using 5bits control words, the tuning error is less than ±1.6%.展开更多
In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world da...In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework.展开更多
随着软件的多样性和复杂性的不断增加,软件漏洞的数量也呈现出爆炸式的增长,同时,软件漏洞的修复也变得越来越困难。漏洞自动修复方法近来得到了研究者的广泛关注,而大型语言模型(Large Language Model, LLM)的出现为漏洞自动修复开辟...随着软件的多样性和复杂性的不断增加,软件漏洞的数量也呈现出爆炸式的增长,同时,软件漏洞的修复也变得越来越困难。漏洞自动修复方法近来得到了研究者的广泛关注,而大型语言模型(Large Language Model, LLM)的出现为漏洞自动修复开辟了新的道路。目前的代码漏洞修复LLM的研究仅仅将漏洞修复归类为通用的文本生成任务,得到修复程序,并定义漏洞自动修复工具生成的修复程序当且仅当其和标准答案完全一致的情况下为有效修复程序。然而,同一个漏洞程序可能对应着多个不同的修复程序,当前判定方法过于苛刻,且代码生成任务不同于一般的文本生成任务,在生成代码时不仅要考虑代码的功能正确性,还需要考虑代码的安全性。由于LLM在预训练过程中使用的代码语料没有安全标签,在生成修复程序时是使用Top-K排序算法基于概率来进行生成,也没有考虑代码的安全性因素,所以,即使生成的修复程序修复了当前漏洞,也有可能会引入新的漏洞。针对这些问题,该文提出了一种基于大模型的软件漏洞自动修复方法,包括提示工程、模型微调技术和关注生成代码安全性的重排序算法SecRerank,从模型的输入、模型本身以及模型的输出等三个阶段来提升模型的漏洞修复性能。实验结果表明,该方法的漏洞修复效果优于基线方法。展开更多
中波广播是我国广播媒体的重要传播载体。其发射机调谐性能直接关系播出质量。针对100 kW中波发射机调谐速度慢、反射功率高、热稳定性差等问题,提出一种基于模糊比例-积分-微分(Proportional Integral Derivative,PID)自适应算法的自...中波广播是我国广播媒体的重要传播载体。其发射机调谐性能直接关系播出质量。针对100 kW中波发射机调谐速度慢、反射功率高、热稳定性差等问题,提出一种基于模糊比例-积分-微分(Proportional Integral Derivative,PID)自适应算法的自动调谐系统。该系统融合阻抗匹配建模与分级优化策略,构建闭环调谐架构,实现谐振参数的毫秒级修正。实验结果表明,调谐时间缩短93.3%,反射功率峰值降低86.7%,系统效率提升14.0%,具备高温与强干扰下的良好健壮性。实际应用显示,所提系统年节省电费11 000元,运维成本降低6 300元,可为中波广播智能化升级提供关键技术支撑。展开更多
文摘A simple on-chip automatic frequency tuning circuit is proposed. The tuning circuit is modified from voltage-controlled filter (VCF) frequency tuning circuit. We utilize an operational transconductance amplifier and a capacitor to from a single-time constant (STC) circuit which can produce a controllable delay time clock to tune the frequency of the filter. It can efficiently reduce the deviations in the 3 dB bandwidth from the variations of PVT (Process, Voltage and Temperature). The design of the STC circuit is simpler than VCF and it has less chip area. The chip has been implanted using TCMC 0.35 μm CMOS technology and the power consumption is less than 9.05 mW.
基金Project supported by the National High Technology Research and Development Program of China(No.2007AA01Z2A7)the 5th Program of Six Talent Summits of Jiangsu Province,China.
文摘A Gm-C complex filter with on-chip automatic tuning for wireless sensor networks is designed and implemented using 0.18 μm CMOS process. This filter is synthesized from a low-pass 5th-order Chebyshev RLC ladder filter prototype by means of capacitors and fully balanced transconductors. A conventional phase-locked loop is used to realize the on-chip automatic tuning for both center frequency and bandwidth control. The filter is centered at 2 MHz with a bandwidth of 2.4 MHz. The measured results show that the filter provides more than 45 dB image rejection while the ripple in the pass-band is less than 1.2 dB. The complete filter including on-chip tuning circuit consumes 4.9 mA with 1.8 V single supply voltage.
文摘A sixth-order Butterworth Gm-C low-pass filter（LPF） with a continuous tuning architecture has been implemented for a wireless LAN（WLAN） transceiver in 0.35μm CMOS technology.An interior node scaling technique has been applied directly to the LPF to improve the dynamic range and the structure of the LPF has been optimized to reduce both the die size and the current consumption.Measurement results show that the filter has 77.5 dB dynamic range,16.3 ns group delay variation,better than 3%cutoff frequency accuracy,and 0 dBm passband IIP3.The whole LPF with the tuning circuit dissipates only 1.42 mA（5 MHz cutoff frequency） or 2.81 mA（10 MHz cutoff frequency） from 2.85 V supply voltage,and only occupies 0.175 mm^2 die size.
基金Supported by the Key Project of the National Natural Science Foundation of China (No.60437030) the Tianjin Natural Science Foundation (No.05YFJMJC01400).
文摘This letter introduces a 4th order active RC complex filter with 1.SMHz center frequency and 1MHz bandwidth. The total harmonic distortion of the filter is less than -60dB and the image rejection ratio is greater than 60dB. A novel technique is also proposed in this letter to automatically adjust the variation of the time constant. The advantages of the proposed method are its high precision and simplicity. Using 5bits control words, the tuning error is less than ±1.6%.
基金supported in part by the National Natural Science Foundation of China under Grant 62171203in part by the Jiangsu Province“333 Project”High-Level Talent Cultivation Subsidized Project+2 种基金in part by the SuzhouKey Supporting Subjects for Health Informatics under Grant SZFCXK202147in part by the Changshu Science and Technology Program under Grants CS202015 and CS202246in part by Changshu Key Laboratory of Medical Artificial Intelligence and Big Data under Grants CYZ202301 and CS202314.
文摘In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework.
文摘随着软件的多样性和复杂性的不断增加,软件漏洞的数量也呈现出爆炸式的增长,同时,软件漏洞的修复也变得越来越困难。漏洞自动修复方法近来得到了研究者的广泛关注,而大型语言模型(Large Language Model, LLM)的出现为漏洞自动修复开辟了新的道路。目前的代码漏洞修复LLM的研究仅仅将漏洞修复归类为通用的文本生成任务,得到修复程序,并定义漏洞自动修复工具生成的修复程序当且仅当其和标准答案完全一致的情况下为有效修复程序。然而,同一个漏洞程序可能对应着多个不同的修复程序,当前判定方法过于苛刻,且代码生成任务不同于一般的文本生成任务,在生成代码时不仅要考虑代码的功能正确性,还需要考虑代码的安全性。由于LLM在预训练过程中使用的代码语料没有安全标签,在生成修复程序时是使用Top-K排序算法基于概率来进行生成,也没有考虑代码的安全性因素,所以,即使生成的修复程序修复了当前漏洞,也有可能会引入新的漏洞。针对这些问题,该文提出了一种基于大模型的软件漏洞自动修复方法,包括提示工程、模型微调技术和关注生成代码安全性的重排序算法SecRerank,从模型的输入、模型本身以及模型的输出等三个阶段来提升模型的漏洞修复性能。实验结果表明,该方法的漏洞修复效果优于基线方法。
