Abstract: For any linear and time-invariant system, its output is the linear convolution between the variable input sequence and the constant system impulse response. When the input is long and the ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...

To address the issues of low accuracy, high dependence on prior knowledge, and poor adaptability in fusing multi-channel features in existing plunger pump fault diagnosis methods, a new method based ...

Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...

To the extent that you’re familiar with magnetostriction, you probably know that it’s what makes big transformers hum, or that it’s what tips you off if you happen to walk out of a store without ...

Collage by Chelsea Beck, New York Public Library, iStock, alamy Covering all the required content in any class is often difficult for teachers, if not impossible. History teachers face this problem ...

Abstract: Electromagnetic propagation through linear dispersive media can be analyzed using the finite-difference time-domain (FDTD) method by employing the recursive convolution (RC) approach to ...

Reflection in .NET is a powerful feature that allows a program to inspect and interact with its own metadata, types, and assemblies at runtime. This capability is part of the System.Reflection ...

Euler Method: The simplest numerical method for solving ODEs, which uses the derivative to project forward. [ y_{n+1} = y_n + h \cdot f(x_n, y_n) ] Heun's Method (Improved Euler Method): A two-step ...