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A systematic review of compressive sensing: Concepts, implementations and applications
Compressive Sensing (CS) is a new sensing modality, which compresses the signal being
acquired at the time of sensing. Signals can have sparse or compressible representation …
acquired at the time of sensing. Signals can have sparse or compressible representation …
Applications of artificial intelligence on the modeling and optimization for analog and mixed-signal circuits: A review
Recently, there have been many studies attempting to take advantage of advancements in
Artificial Intelligence (AI) in Analog and Mixed-Signal (AMS) circuit design. Automated circuit …
Artificial Intelligence (AI) in Analog and Mixed-Signal (AMS) circuit design. Automated circuit …
Hardware Trojan attacks: Threat analysis and countermeasures
Security of a computer system has been traditionally related to the security of the software or
the information being processed. The underlying hardware used for information processing …
the information being processed. The underlying hardware used for information processing …
Stochastic testing method for transistor-level uncertainty quantification based on generalized polynomial chaos
Uncertainties have become a major concern in integrated circuit design. In order to avoid the
huge number of repeated simulations in conventional Monte Carlo flows, this paper presents …
huge number of repeated simulations in conventional Monte Carlo flows, this paper presents …
Underdesigned and opportunistic computing in presence of hardware variability
Microelectronic circuits exhibit increasing variations in performance, power consumption,
and reliability parameters across the manufactured parts and across use of these parts over …
and reliability parameters across the manufactured parts and across use of these parts over …
Machine learning applications in IC testing
HG Stratigopoulos - … IEEE 23rd European Test Symposium (ETS …, 2018 - ieeexplore.ieee.org
In recent years, a large number of works have surfaced demonstrating applications of
machine learning in the field of integrated circuit testing. Many of these works showcase the …
machine learning in the field of integrated circuit testing. Many of these works showcase the …
Bayesian model fusion: large-scale performance modeling of analog and mixed-signal circuits by reusing early-stage data
Efficient high-dimensional performance modeling of today's complex analog and mixed-
signal (AMS) circuits with large-scale process variations is an important yet challenging task …
signal (AMS) circuits with large-scale process variations is an important yet challenging task …
Experience of data analytics in EDA and test—principles, promises, and challenges
LC Wang - IEEE Transactions on Computer-Aided Design of …, 2016 - ieeexplore.ieee.org
Applying modern data mining in electronic design automation and test has become an area
of growing interest in recent years. This paper reviews some of the recent developments in …
of growing interest in recent years. This paper reviews some of the recent developments in …
Review on compressive sensing algorithms for ECG signal for IoT based deep learning framework
SS Kumar, P Ramachandran - Applied Sciences, 2022 - mdpi.com
Nowadays, healthcare is becoming very modern, and the support of Internet of Things (IoT)
is inevitable in a personal healthcare system. A typical personal healthcare system acquires …
is inevitable in a personal healthcare system. A typical personal healthcare system acquires …
WDP-BNN: Efficient wafer defect pattern classification via binarized neural network
Q Zhang, Y Zhang, J Li, Y Li - Integration, 2022 - Elsevier
Wafer map defect pattern classification using convolutional neural network (CNN) has
gained a lot of attention in recent years but it demands huge computation and memory cost …
gained a lot of attention in recent years but it demands huge computation and memory cost …