Abstract: In this study, to obtain Born approximation multi-resolution imaging for transient electromagnetic (TEM) pseudo wavefield, employing a series of differential pulse with multiple pulse widths ...

Abstract: This paper designs a close loop Σ-Δ readout circuit for differential MEMS accelerometer. A technique named oversampling successive approximation (OSA) is ...

Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...

This paper proposes a new deep-learning-based algorithm for high-dimensional Bermudan option pricing. To the best of our knowledge, this is the first study of the arbitrary-order discretization scheme ...

Simo Särkkä and Arno Solin (2019). Applied Stochastic Differential Equations. Cambridge University Press. Cambridge, UK. The book can be ordered through Cambridge University Press or, e.g., from ...

The control of general nonlinear systems is a challenging task in particular for large-scale models as they occur in the semi-discretization of partial differential equations (PDEs) of, say, fluid ...

This research work investigates the use of Artificial Neural Network (ANN) based on models for solving first and second order linear constant coefficient ordinary differential equations with initial ...

Partial differential equations (PDEs) are among the most ubiquitous tools used in modeling problems in nature. However, solving high-dimensional PDEs has been notoriously difficult due to the “curse ...

1 Department of Computer Science and Information Systems, University of Wisconsin River Falls, River Falls, WI, USA. 2 Department of Mathematics, Statistics and Computer Science, University of ...

The fully differential amplifier (FDA) has emerged as a very popular last-stage interface to differential-input analog-to-digital converters (ADCs) spanning the range from 24-bit delta-sigma, 18- to ...