Book Abstract: In 1971 Dr. Paul C. Lauterbur pioneered spatial information encoding principles that made image formation possible by using magnetic resonance signals. Now Lauterbur, "father of the MRI ...

Book Abstract: This advanced text and reference covers the design and implementation of integrated circuits for analog-to-digital and digital-to-analog conversion. It begins with basic concepts and ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

Abstract: Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the ...

Abstract: Deadbeat predictive current control (DPCC) has been widely applied in permanent magnet synchronous motor (PMSM) drives due to its fast dynamic response and good steady-state performance.

Abstract: We consider the problem of partitioning the nodes of a graph with costs on its edges into subsets of given sizes so as to minimize the sum of the costs on all edges cut. This problem arises ...

Abstract: Real-time image dehazmg is crucial for applications such as autonomous driving, surveillance, and remote sensing, where haze can significantly reduce visibility. However, many deep learning ...

This book presents an original generalized transmission line approach associated with non-resonant structures that exhibit larger bandwidths, lower loss, and higher design flexibility. It is based on ...

Abstract: Fetal cerebellum landmark detection is crucial for assessing fetal brain development. Although deep learning has become the standard for automatic landmark detection, most previous methods ...

Abstract: This paper presents an output-capacitorless low-dropout regulator (OCL-LDO), merging with a hybrid push-pull buffer. The hybrid push-pull buffer implements a dynamic and adaptive biasing ...

Abstract: Object detection methods using deep convolutional neural networks (CNNs) have derived major advances in normal images. However, such success is hardly achieved with adverse weather due to a ...

Abstract: Type-2 fuzzy neural networks (T2FNNs) are particularly effective in dealing with nonlinear systems. However, they inevitably suffer from multicollinearity problems caused by the significant ...