Science China Information Sciences最新文献

{"title":"High precision current mirror circuit based on two-dimensional material transistors","authors":"Shiping Gao, Chen Pan, Pincheng Su, Xing-Jian Yangdong, Wentao Yu, Zhoujie Zeng, Yu Shen, Jingwen Shi, Yanwei Cui, Pengfei Wang, Yuekun Yang, Cong Wang, Bing Cheng, Shi-Jun Liang, Feng Miao","doi":"10.1007/s11432-024-4083-6","DOIUrl":"https://doi.org/10.1007/s11432-024-4083-6","url":null,"abstract":"<p>We first report a 2D material-based P-FET with excellent output current saturation characteristics and demonstrate the highest small-signal output impedance characteristics among all previously published 2D-FETs. Further, we utilize the excellent performance of the device to demonstrate a current mirror circuit, which has better high precision current replication performance than silicon-based devices. This work provides a possible technical approach for the development of high-performance analog circuit devices based on 2D materials.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"1 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BioKG-CMI: a multi-source feature fusion model based on biological knowledge graph for predicting circRNA-miRNA interactions","authors":"Mengmeng Wei, Lei Wang, Yang Li, Zhengwei Li, Bowei Zhao, Xiaorui Su, Yu Wei, Zhuhong You","doi":"10.1007/s11432-024-4098-3","DOIUrl":"https://doi.org/10.1007/s11432-024-4098-3","url":null,"abstract":"<p>This study proposes a model named BioKG-CMI to predict CMIs based on a biological knowledge graph. Faced with limited data, we employ subcellular localization to generate negative samples that align more closely with biological logic. To mine semantic information in circRNA and miRNA sequences, we introduce the pre-trained model BERT to learn sequence feature representation. Guided by the hypothesis that adjacent molecules have similar functions, we calculate spatial proximity between nodes of the same class. The DisMult algorithm is applied to extract the potential logical rules of the knowledge graph and learn entity and relationship representations. Subsequently, the integration of multi-feature successfully addresses the challenge of expressing the complex biological knowledge graph and overcoming the limitation of single-feature inadequacy. Multiple comparative experiments and case studies demonstrate the robustness of the proposed model.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"167 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SeeMore: a spatiotemporal predictive model with bidirectional distillation and level-specific meta-adaptation","authors":"Yuqing Ma, Wei Liu, Yajun Gao, Yang Yuan, Shihao Bai, Haotong Qin, Xianglong Liu","doi":"10.1007/s11432-022-3859-8","DOIUrl":"https://doi.org/10.1007/s11432-022-3859-8","url":null,"abstract":"<p>Predicting future frames using historical spatiotemporal data sequences is challenging and critical, and it is receiving a lot of attention these days from academic and industrial scholars. Most spatiotemporal predictive algorithms ignore the valuable backward reasoning ability and the disparate learning complexities among different layers and hence, cannot build good long-term dependencies and spatial correlations, resulting in suboptimal solutions. To address the aforementioned issues, we propose a two-stage coarse-to-fine spatiotemporal predictive model with bidirectional distillation and level-specific meta-adaptation (SeeMore) in this paper, which includes a bidirectional distillation network (BDN) and a level-specific meta-adapter (LMA), to gain bidirectional multilevel reasoning. In the first stage, BDN concentrates on bidirectional dynamics modeling and coarsely constructs spatial correlations of different layers, while LMA is introduced in the second fine-tuning stage to refine the multilevel spatial correlations from a meta-learning perspective. In particular, BDN mimics the forward and backward reasoning abilities of humans in a distillation manner, which aids in the development of long-term dependencies. The LMA views learning of different layers as disparate but related tasks and guides the transfer of learning experiences among these tasks through learning complexities. Thus, each layer could be closer to its solutions and could extract more informative spatial correlations. By capturing the enhanced short-term spatial correlations and long-term temporal dependencies, the proposed model could extract adequate knowledge from sequential historical observations and accurately predict future frames whose backtracking preconditions are consistent with the historical sequence. Our work is general and robust enough to be integrated into most spatiotemporal predictive models without requiring additional computation or memory cost during inference. Extensive experiments on four widely used predictive learning benchmarks validated the proposed model’s effectiveness in comparison to state-of-the-art approaches (e.g., 10.6% improvement of Mean Squared Error on the Moving MNIST dataset).</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"41 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Skill enhancement learning with knowledge distillation","authors":"Naijun Liu, Fuchun Sun, Bin Fang, Huaping Liu","doi":"10.1007/s11432-023-4016-0","DOIUrl":"https://doi.org/10.1007/s11432-023-4016-0","url":null,"abstract":"<p>Skill learning through reinforcement learning has significantly progressed in recent years. However, it often struggles to efficiently find optimal or near-optimal policies due to the inherent trial-and-error exploration in reinforcement learning. Although algorithms have been proposed to enhance skill learning efficacy, there is still much room for improvement in terms of skill learning performance and training stability. In this paper, we propose an algorithm called skill enhancement learning with knowledge distillation (SELKD), which integrates multiple actors and multiple critics for skill learning. SELKD employs knowledge distillation to establish a mutual learning mechanism among actors. To mitigate critic overestimation bias, we introduce a novel target value calculation method. We also perform theoretical analysis to ensure the convergence of SELKD. Finally, experiments are conducted on several continuous control tasks, illustrating the effectiveness of the proposed algorithm.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"35 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-agent policy transfer via task relationship modeling","authors":"Rongjun Qin, Feng Chen, Tonghan Wang, Lei Yuan, Xiaoran Wu, Yipeng Kang, Zongzhang Zhang, Chongjie Zhang, Yang Yu","doi":"10.1007/s11432-023-3862-1","DOIUrl":"https://doi.org/10.1007/s11432-023-3862-1","url":null,"abstract":"<p>Team adaptation to new cooperative tasks is a hallmark of human intelligence, which has yet to be fully realized in learning agents. Previous studies on multi-agent transfer learning have accommodated teams of different sizes but heavily relied on the generalization ability of neural networks for adapting to unseen tasks. We posit that the relationship among tasks provides key information for policy adaptation. We utilize this relationship for efficient transfer by attempting to discover and exploit the knowledge among tasks from different teams, proposing to learn an effect-based task representation as a common latent space among tasks, and using it to build an alternatively fixed training scheme. Herein, we demonstrate that task representation can capture the relationship among teams and generalize to unseen tasks. Thus, the proposed method helps transfer the learned cooperation knowledge to new tasks after training on a few source tasks. Furthermore, the learned transferred policies help solve tasks that are difficult to learn from scratch.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"5 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of chiplet-based design: system architecture and interconnection","authors":"Yafei Liu, Xiangyu Li, Shouyi Yin","doi":"10.1007/s11432-023-3926-8","DOIUrl":"https://doi.org/10.1007/s11432-023-3926-8","url":null,"abstract":"<p>Chiplet-based design, which breaks a system into multiple smaller dice (or “chiplets”) and reassembles them into a new system chip through advanced packaging, has received extensive attention in the post Moore’s law era due to its advantages in terms of cost, performance, and agility. However, significant challenges arise in this implementation approach, including the mapping of functional components onto chiplets, co-optimization of package and architecture, handling the increased latency of communication across functions in different dies, the uncertainty problems of fragment communication subsystems, such as maintaining deadlock-free when independently designed chiplets are combined. Despite various design approaches that attempt to address these challenges, surveying these approaches one-after-another is not the most helpful way to offer a comparative viewpoint. Accordingly, in this paper, we present a more comprehensive and systematic strategy to survey the various approaches. First, we divide them into chiplet-based system architecture design and interconnection design, and further classify them based on different architectures and building blocks of interconnection. Then, we analyze and cross-compare each classification separately, and in addition, we present a topical discussion on the evolution of memory architectures, design automation, and other relevant topics in chiplet-based designs. Finally, some discussions on important topics are presented, emphasizing future needs and challenges in this rapidly evolving field.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"47 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 56 Gb/s DAC-DSP-based transmitter with adaptive retiming clock optimization using inverse-PR-based PD achieving 8-UI converge time in 28-nm CMOS","authors":"Shubin Liu, Chenxi Han, Xiaoteng Zhao, Yuhao Zhang, Shixin Li, Hongzhi Liang, Lihong Yang, Zhangming Zhu","doi":"10.1007/s11432-024-4072-9","DOIUrl":"https://doi.org/10.1007/s11432-024-4072-9","url":null,"abstract":"<p>This work presents an adaptive clock optimization scheme for TX to alleviate the timing constraints for the retimer. Using the PR and inverse-PR-based phase detector, the optimal clock phase is selected for retiming with only 8 UI convergence time. By adopting the proposed technique, we realize a 1–56 Gb/s DAC-DSP-based TX in 28-nm CMOS. Measurement results show that the rising edge of retiming clock is located in the center of data when the phase adjustment completed. The total TX consumes 164 mWat 56-Gb/s PAM4 signaling with 97.8% RLM in 0.25 mm² area. Therefore, the proposed retiming clock optimization scheme is a promising scheme for high-speed TX.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"9 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 10-GS/s 8-bit 2× time interleaved hybrid ADC with λ/4 reference T-Line sharing technique","authors":"Zhangming Zhu, Jun Chang, Hongzhi Liang, Ruixue Ding, Shubin Liu","doi":"10.1007/s11432-024-4082-9","DOIUrl":"https://doi.org/10.1007/s11432-024-4082-9","url":null,"abstract":"<p>A 10-GS/s 8-bit 2× time interleaved hybrid ADC with λ/4 reference T-Line sharing technique has been demonstrated. Meanwhile, an on-chip 5th HILO with a center frequency of 20 GHz is embedded to generate the low-jitter propagation signal for T-Lines. The proposed sharing reference T-Line technique and serpentine routing enable a significant improvement on silicon-area efficiency. The ADC achieves a measured 3-dB effective bandwidth close to 6.7 GHz and an ENOB exceeding 5.5. The hybrid ADC chip fabricated in 0.9-V 28-nm CMOS achieves a 10-GS/s sampling frequency with a 31.22-mW power consumption. At Nyquist input, the SNDR is 38.11 dB, while at over-Nyquist 7.89 GHz input, the SNDR is 34.2 dB.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"74 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A CSP-based retraining framework for motor imagery based brain-computer interfaces","authors":"Xue Jiang, Lubin Meng, Xinru Chen, Dongrui Wu","doi":"10.1007/s11432-024-4081-x","DOIUrl":"https://doi.org/10.1007/s11432-024-4081-x","url":null,"abstract":"<p>CSP is one of the most widely used signal processing approaches in EEG-based MI classification; however, the CSP optimization objective is not completely consistent with the final classification objective, and hence it does not necessarily lead to the best classification performance. This study has proposed a retraining framework, which retrains a neural network with the same forward computational process and initial parameters as the CSP-based traditional model, and further optimizes it on the labeled training data using gradient descent. Experiments on four MI datasets demonstrated that retraining improved traditional models’ classification performance and outperformed several popular deep neural network models, especially when the amount of labeled training data was very small. Our work demonstrates the advantage of integrating knowledge from traditional models and from the training data in EEG-based BCIs.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"43 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tuning the ferroelectricity of Hf0.5Zr0.5O2 with alloy electrodes","authors":"Keqin Liu, Bingjie Dang, Zhiyu Yang, Teng Zhang, Zhen Yang, Jinxuan Bai, Zelun Pan, Ru Huang, Yuchao Yang","doi":"10.1007/s11432-023-3932-2","DOIUrl":"https://doi.org/10.1007/s11432-023-3932-2","url":null,"abstract":"<p>Tuning ferroelectricity of Hf_0.5Zr_0.5O₂ is crucial for facilitating its practical applications in various fields, including in-memory and neuromorphic computing. Previous studies have revealed that the electrodes have a significant influence on ferroelectricity, and changing electrode materials can realize different but discrete ferroelectric polarization values. Here, we introduce an alloy-electrode method, in order to achieve gradual and accurate modulation of ferroelectric polarization, especially useful for matching the polarization charges at the interface of ferroelectric insulators and ferroelectric semiconductors. Au and W electrodes are chosen as baselines for realizing weak and strong ferroelectric polarization, where the intermediate states can be achieved by adjusting the ratio of metals in the Au-W alloy. To demonstrate the generality of this approach, the Cu-W alloy electrode is also realized for tuning ferroelectric polarization. The effect of alloy electrodes on device leakage current, endurance, and retention is evaluated. In addition, the temperature stability of ferroelectric capacitors is tested, where limited changes in both remnant polarization and coercive voltages are observed, showing the great potential of the ferroelectric hafnium oxide. Such gradual modulation of ferroelectric polarization could facilitate the application of Hf_0.5Zr_0.5O₂ in in-memory and neuromorphic computing.</p>","PeriodicalId":21618,"journal":{"name":"Science China Information Sciences","volume":"55 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}