Related Experiment Video

Updated: Mar 16, 2026

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples
07:01

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

10.0K

Electro-magnetic analysis of high-frequency digital signal processors

Bing Li1, Mingzhu Lei1, Meiyuan Chen1

  • 1College of Automation, Harbin Engineering University, Heilongjiang, China.

Springerplus
|August 23, 2016
PubMed

Keywords:
DipoleElectro-magnetic radiationHigh-frequency digital processorsPrediction analysis

More Related Videos

Studying Cavitation Enhanced Therapy07:36

Studying Cavitation Enhanced Therapy

Published on: April 9, 2021

5.9K
Generation and Coherent Control of Pulsed Quantum Frequency Combs06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.8K

Related Concept Videos

Design Example01:23

Design Example

The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
622
Frequency Response of BJT01:24

Frequency Response of BJT

The frequency response of a Bipolar Junction Transistor (BJT) in a common-emitter configuration is critical to its functionality, especially in applications involving amplification of alternating current (AC) signals. This response can be analyzed through low-frequency and high-frequency equivalent circuits, considering various internal parameters and external conditions.
Low-Frequency Response: At low frequencies, the behavior of the BJT is determined by its DC bias point, which is set by the...
1.5K
Discrete-Time Fourier Series01:20

Discrete-Time Fourier Series

The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
810
Small-Signal Analysis of MOSFET Amplifiers01:23

Small-Signal Analysis of MOSFET Amplifiers

In small-signal analysis, a MOSFET transistor amplifier acts as a linear amplifier when operating in its saturation region. The gate-to-source voltage (VGS) of the MOSFET is the sum of the DC biasing voltage and the small time-varying input signal. This combination sets up the operating point and modulates the drain current (ID) that flows from the drain to the source. When a small AC signal is superimposed on the DC bias voltage at the gate, the instantaneous drain current comprises three...
1.2K
Network Function of a Circuit01:25

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
984
Fast Fourier Transform01:10

Fast Fourier Transform

The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
1.1K