Bessenrodt and Ono, Chen, Wang and Jia, DeSalvo and Pak were the first to discover the log-subadditivity, log-concavity, and the third-order Turán inequality of partition function, respectively. Many other import...
Asynchronous circuits have recently become more popular in Internet of Things (IoT) and neural network chips because of their potential low power consumption. However, due to the lack of Electronic Design Automation (...
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ISBN:
(数字)9783981926385
ISBN:
(纸本)9798350348606
Asynchronous circuits have recently become more popular in Internet of Things (IoT) and neural network chips because of their potential low power consumption. However, due to the lack of Electronic Design Automation (EDA) tools, the asynchronous circuits design efficiency remains low and faces challenges in large-scale applications. This paper proposes a new asynchronous circuits design flow using traditional EDA tools, and applies a new backward delay propagation constraint (BDPC) method. In this method, control paths and data paths are tightly coupled and analyzed together to improve the accuracy of static timing analysis. Compared to previous works, the proposed design flow and constraint method offer significant advantages in terms of accuracy and efficiency. To verify this flow, an asynchronous RISC-V processor was implemented on TSMC 65nm process. Compared to synchronous version, asynchronous processor achieves a power optimization of 17.4 % while main-taining the same speed and area.
In this paper,a parking slot detection algorithm based on a bird's eye view is proposed.A density-based spatial clustering of applications with noise(DBSCAN) clustering algorithm and template matching algorithm ar...
In this paper,a parking slot detection algorithm based on a bird's eye view is proposed.A density-based spatial clustering of applications with noise(DBSCAN) clustering algorithm and template matching algorithm are fused to detect parking slots in a bird's eye *** probabilistic Hough line detection and an improved DBS CAN clustering algorithm is developed to locate the sidelines of parking ***,template matching is provided to locate and classify the "T shape" and "L shape" marking points more ***,the marking points and sidelines of parking slots are integrated to complete the parking slot *** recall rate and precision rate of experimental results are 74.4% and 92.0%.
In the field of hyperspectral unmixing, deep learning has received increasing attention due to its powerful learning and data representation capabilities. Autoencoder is a popular technique for unmixing. Recently, an ...
In the field of hyperspectral unmixing, deep learning has received increasing attention due to its powerful learning and data representation capabilities. Autoencoder is a popular technique for unmixing. Recently, an autoencoder-based depth image prior algorithm has been proposed for hyperspectral unmixing, which employs geometric methods to extract endmembers. The performance of this network solely focuses on estimating the abundance of images, and it has achieved good unmixing results. However, the depth image only employs one core network, which makes it highly vulnerable to noise and can lead to unstable unmixing outcomes. To address the aforementioned issue, this paper proposes a collaborative consistency autoencoder-based hyperspectral unmixing approach with deep image prior (CCAUDIP). For the proposed CCAUDIP model, it adopts two autoencoders to cooperatively handle the same input data to enhance the generalization ability of the network. Additionally, a consistency constraint is introduced to restrict the abundance outputs of the two core autoencoders and improve the robustness of the network. The experimental results show that the CCAUDIP method can achieve better unmixing results compared to other advanced unmixing algorithms.
In this paper,a delta operator opinion dynamics model is established in social networks with antagonistic *** opinion interactions of all individuals in the antagonistic social networks are characterized as a delta op...
In this paper,a delta operator opinion dynamics model is established in social networks with antagonistic *** opinion interactions of all individuals in the antagonistic social networks are characterized as a delta operator dynamics system with *** is analyzed for the delta operator opinion dynamics model based on Lyapunov methods in delta *** results are given to illustrate effectiveness of the theoretical results for the delta operator opinion dynamics model.
Data-driven deep learning models are constrained by the scale and diversity of training data, making them vulnerable to data bias. While large language models (LLMs) exhibit superior generalization in vulnerability de...
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ISBN:
(数字)9798331533113
ISBN:
(纸本)9798331533120
Data-driven deep learning models are constrained by the scale and diversity of training data, making them vulnerable to data bias. While large language models (LLMs) exhibit superior generalization in vulnerability detection, their low inference efficiency and high computational costs hinder practical deployment in industrial settings. To address these limitations, we propose AIDetectVul, a novel vulnerability detection framework leveraging feature fusion from pre-trained models. Our approach concurrently utilizes encoder-only and decoder-only architectures to extract complementary code embeddings, with feature fusion enhancing semantic diversity. These enriched representations are then processed by a Transformer model, where the self-attention mechanism effectively captures long-range code dependencies, ultimately improving both detection accuracy and generalization capability. Comprehensive evaluations on proprietary enterprise datasets and open-source benchmarks demonstrate that AIDetectVul achieves comparable detection accuracy to the state-of-the-art LineVul model while demonstrating measurable improvements in generalization performance. Compared to LLM-based approaches, our solution maintains significantly lower computational overhead and training costs, making it particularly suitable for industrial applications.
The challenge in image-based visual servoing is to deal with the visibility constraints, which require the image features to always remain in the field of view (FOV) of the camera. In this paper, a novel constraint fu...
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With the development of real-time requirements for Synthetic Aperture Radar (SAR) imaging technology, SAR imaging processing SoC (System on Chip) has become an important research field at present. The subsystem for SA...
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ISBN:
(数字)9798331515669
ISBN:
(纸本)9798331515676
With the development of real-time requirements for Synthetic Aperture Radar (SAR) imaging technology, SAR imaging processing SoC (System on Chip) has become an important research field at present. The subsystem for SAR imaging processing in the SAR imaging SoC needs to be fully verified during the development process. This article designs a UVM-based random verification environment, focusing on the verification requirements of key computing engines and interaction engines in the SAR imaging processing SoC. At the same time, a modeling method for computing engines and interaction engines is proposed, which can quickly and accurately describe the functions and behaviors of processing engines. Collaborating with the verification environment and the reference C model, the design under test achieves satisfactory coverage results. Consequently, the functionality of the processing engines within the subsystem can be comprehensively and effectively verified. The content studied in this article has certain value for the engineering verification implementation of SAR imaging algorithms in the SoC.
In the Low Earth Orbit (LEO) satellite Internet of Things (IoT), there is a significant imbalance in the distribution of ground terminal locations. Under a fixed beam regime, this leads to scenarios where satellite ne...
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ISBN:
(数字)9798350386943
ISBN:
(纸本)9798350386950
In the Low Earth Orbit (LEO) satellite Internet of Things (IoT), there is a significant imbalance in the distribution of ground terminal locations. Under a fixed beam regime, this leads to scenarios where satellite network capacity is simultaneously overloaded and underutilized, resulting in low capacity utilization rates for LEO satellite-to-earth communications. Distributed LEO-MIMO (Low Earth Orbit-Multiple Input Multiple Output) can alleviate overloads and distribute capacity by extending the satellite beam coverage area. However, unlike terrestrial distributed MIMO, which faces co-channel interference issues, distributed satellite networking in LEO systems also deals with the heterogeneity of Doppler shifts across different satellite links. To address these issues, a distributed LEO-MIMO linear precoding update algorithm is proposed. This paper, utilizing spectral graph theory, reduces the problem of constructing a single-frame precoding matrix to a graph signal correlation calculation problem. We introduce a precoding solving algorithm based on a time sliding window, which enhance data processing efficiency and reduce communication latency.
Global routing is a crucial step in the design of Very Large-Scale Integration (VLSI) circuits. However, most of the existing methods are heuristic algorithms, which cannot conjointly optimize the subproblems of globa...
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