Efficient and accurate channel estimation with low pilot overhead is essential for massive multiple-input multiple-output (MIMO) wireless communication systems to achieve high spectral and energy efficiency. This work...
详细信息
Generative artificial intelligence (GenAI) is rapidly driving a new phase of artificial intelligence revolution, marked by various applications such as ChatGPT, Sora and DeepSeek. With powerful capabilities in content...
详细信息
This paper introduces the design of a type of power amplifier working in the Kaband,which has three stages based on 45nm CMOS *** operating frequency is 25-27GHz,and it has good efficiency and *** them,the driving sta...
详细信息
This paper introduces the design of a type of power amplifier working in the Kaband,which has three stages based on 45nm CMOS *** operating frequency is 25-27GHz,and it has good efficiency and *** them,the driving stage adopts a cascode structure,the power stage adopts common source structure,and the matching network adopts a transformer *** Cadence Virtuoso for simulation at the operating voltage of 1.8V,power gain of the single-ended power amplifier is 44.76 dB,saturation output power is 14.66 dBm,the output power at the 1dB compression point is 12.9dBm,and corresponding power-added efficiency is 22.19%.
Passive Optical Network (PON) standards relied on Time Division Multiplexing (TDM) and Wavelength Division Multiplexing (WDM) methods to maximize data rate. The latest 25GS-PON specifications were declared by Multi-So...
详细信息
Predicting interactions between proteins is one of the most important yet challenging problems in structural bioinformatics. Intrinsically, potential function sites in protein surfaces are determined by both geometric...
详细信息
In the modern era of information explosion, where there is enormous information including thousands and millions of texts loaded on the Internet of over 1.2 million terabytes, there are no accurate statistics on the s...
详细信息
Remote sensing scene classification is growing fast in demand and application within the Earth Observation domain. Satellite Image data are usually high resolution but low in number. DenseNet architectures are quite p...
Remote sensing scene classification is growing fast in demand and application within the Earth Observation domain. Satellite Image data are usually high resolution but low in number. DenseNet architectures are quite powerful and achieve good accuracy in this task even without large-scale pretraining from ImageNet-like datasets. But, DenseNet lacks efficiency and is considered a quite heavy model by modern standards. We propose DenseNetx, a family of efficient densenet architecture which can dramatically reduce computation costs while outperforming the baseline model. In short, we use a larger input size while aggressively downsampling in the stem block using two $3\times 3$ convolutions of stride 2, and use large-kernel depthwise-separable convolution in the denselayer to achieve higher efficiency. Our results on the WHU-RS19 and Optima1-31 scene classification datasets show that our model can outperform the baseline at 20% reduced parameters and 53% fewer flops, while achieving up to 4.5% increased accuracy with a larger input while retaining efficiency.
Corrugated silicon nitride masks (SiNMs) with improved mechanical strength are developed for patterning OLED microdisplays. The corrugations in the nitride membrane significantly increase the rigidity of the mask and ...
详细信息
Time-Sensitive Networking (TSN) has emerged as a promising communication technology for automotive applications. The TSN standards provide a flexible toolkit, enabling network designers to select the features and mech...
Time-Sensitive Networking (TSN) has emerged as a promising communication technology for automotive applications. The TSN standards provide a flexible toolkit, enabling network designers to select the features and mechanisms that best suit the application context requirements. TSN facilitates the management of diverse traffic flows through a single channel by defining transmission schemes and protocols. However, some automotive applications, such as the automated driving ones, require the support for event-driven real-time traffic, but the TSN support for this kind of flows is limited. To overcome this limitation, a recent research proposed an online Earliest Deadline First-based scheduling approach, called Deadline-TSN, able to handle various traffic classes (including the event-driven ones) in a uniform way. Deadline-TSN supports real-time traffic, but is not designed to support deterministic communications. For this reason, this paper investigates the adoption of TSN to build network setups for managing diverse kinds of in-car traffic flows, i.e., periodic and event-driven, with diverse timing constraints and presents a comparative performance evaluation between a configuration exploiting a combination of multiple TSN transmission schemes and Deadline-TSN in a realistic automotive scenario.
Safety has always been the primary consideration in high-speed railway *** are one of the most safety-critical components in the railway system,yet its fault diagnosis still relies on manual inspections,which is time-...
详细信息
Safety has always been the primary consideration in high-speed railway *** are one of the most safety-critical components in the railway system,yet its fault diagnosis still relies on manual inspections,which is time-consuming and can lead to missing reports of turnout *** paper proposes an automatic turnout fault diagnosis method based on group decision *** assembling three individual classification algorithms,including the k-nearest neighbors algorithm,naive Bayes classifier,and deep neural network,this algorithm aims to automate turnout fault diagnosis and reduce the possibility of missing *** to compare the performance of the group decision making algorithm and the three individual classifiers based on datasets generated by real turnout systems in simulated fault conditions are carried *** result shows that the recall,i.e.,the sensitivity to turnout fault of this algorithm is superior to the individual classifiers without losing overall accuracy,indicating that the missing report rate can be reduced through the group decision making process.
暂无评论