The logic blocks in FPGAs are configured to realize complex combinational functions describing the operation of different functional units of combinational type: encoders, decoders, multiplexers, demultiplexers, code converters, digital comparators and various arithmetic circuits. One of the issues ...
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The concept of a DT surpasses that of a digital model, as demonstrated in Fig.1. A digital model enables a unidirectional flow of data, originating from the physical object and feeding into its digital representation. The digital model adjusts itself based on input from the physical asset, wi...
This method is based on counting the number of encoder pulses [x(k)−x(k−1)][x(k)−x(k−1)] in an established period of time (T) which can be defined as the inverse of the DSP calculation rate (150 MHz in our case) [22]. The encoder count (position) is read at ...
A novel 4D dual-memristor chaotic system (4D-DMCS) is constructed by concurrently introducing two types of memristors: an ideal quadratic smooth memristor and a memristor with an absolute term, into a newly designed jerk chaotic system. The excellent nonlinear properties of the system are investigat...
Machine learning (ML) has evolved as a technology used in even broader domains, ranging from spam detection to space exploration, as a result of the boom i
In Depth 4.7.3 Device List 4.7.4 Hardware Platforms and Software Examples 4.7.5 Documentation 5Interface Key Technologies 5.1 Direct Host Control of C2000 Peripherals 5.1.1 Value Proposition 5.1.2 In Depth 5.1.2.1 HIC Bridge for FSI Applications 5.1.2.2 HIC Bridge for Position Encoder ...
[88] proposed a hybrid prediction method, which combines the average Euclidean distance, the transfer learning method based on stacked noise reduction automatic encoder and the improved Arrhenius model. The model estimates the life of the same battery formulation tested at high temperature, and ...
The deep spectral features were represented using a sparse-auto-encoder (SAE) and CNN was applied to extract image features. After fusing the extracted features, machine learning algorithms such as k-nearest neighbors (KNN) and SVM are used for classification. The results showed that the SAE-...
Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology. CNN is designed to automatically and adaptively learn spatial hierarchies of features through back...