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Related Concept Videos

Superposition Theorem for AC Circuits01:13

Superposition Theorem for AC Circuits

Consider encountering a circuit in a steady state where all its inputs are sinusoidal, yet they do not all possess the same frequency. Such a circuit is not classified as an alternating current (AC) circuit, and consequently, its currents and voltages will not exhibit sinusoidal behavior. However, this circuit can be analyzed using the principle of superposition.
The principle of superposition stipulates that the output of a linear circuit with several concurrent inputs is equivalent to the...
Impulse Response01:17

Impulse Response

The impulse response is the system's reaction to an input impulse. In an RC circuit, the voltage source is the input, and the capacitor's voltage is the output. The system's state and output response before and after input excitation are distinctly defined.
Kirchhoff's law forms an input signal equation, with the capacitor's current and voltage providing the output. Substituting the current and dividing by RC yields a differential equation. The output for an impulse input is the impulse...
Superposition Theorem01:18

Superposition Theorem

The superposition principle is a fundamental concept stating that in a linear circuit, the voltage across (or current through) an element can be determined by summing the individual contributions of each independent source acting in isolation. When dealing with linear circuits containing multiple independent sources, this principle serves as a valuable tool for analysis. To apply the superposition principle effectively, one should focus on a single independent source at a time while...
The Power Superposition Principle01:19

The Power Superposition Principle

Consider a circuit with two sinusoidal voltage sources. Each one influences the circuit independently, and the superposition principle helps us understand the combined effect by adding up the responses from each source.
Deconvolution01:20

Deconvolution

Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...

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A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

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Finite impulse response utilizing the principle of superposition.

S E Carter1, D C Malocha

  • 1Dept. of Electr. and Comput. Eng., Central Florida Univ., Orlando, FL.

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
|January 1, 1997
PubMed
Summary

A new finite impulse response (FIR) filter design algorithm offers a simpler, more efficient method for optimizing filter length and specifications. This approach reduces computational complexity compared to existing FIR design techniques.

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Area of Science:

  • Digital Signal Processing
  • Filter Design

Background:

  • Optimizing finite impulse response (FIR) filter length is crucial for reducing filter size and computational load.
  • Existing FIR design algorithms include Remez exchange, linear programming, and least mean squares, each with limitations.

Purpose of the Study:

  • To introduce a novel, efficient, and accurate algorithm for designing FIR filters with arbitrary specifications.
  • To present a technique for tailoring passband and stopband responses for near-optimum time length.

Main Methods:

  • Definition of basic functions for the design process.
  • Overview of the FIR filter design procedure.
  • Presentation of a technique for achieving tailored frequency responses and near-optimum time length.

Main Results:

  • The new algorithm demonstrates simplicity, efficiency, and accuracy in FIR filter design.
  • It requires fewer computations than many existing FIR approaches.
  • The design is applicable to compensating for second-order effects in surface acoustic wave (SAW) devices.

Conclusions:

  • The developed FIR design algorithm provides a valuable alternative for creating efficient digital filters.
  • It offers advantages in computational efficiency and design flexibility for specific applications like SAW devices.