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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...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Load-frequency control01:28

Load-frequency control

Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
Linear time-invariant Systems01:23

Linear time-invariant Systems

A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...

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Related Experiment Video

Updated: May 14, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
08:30

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

A DR-ℓ1-PRLS Approach to Adaptive Equalization in Single-Carrier UWA Communication.

Xiao-Chen Chen1, Guan-Quan Dai1,2, Yang Shi1

  • 1College of Navigation, Jimei University, Xiamen 361021, China.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

A new algorithm, data reuse-based ℓ1-regularized proportionate recursive least-squares (DR-ℓ1-PRLS), enhances underwater acoustic communication equalization. It improves accuracy and bit error rate in sparse channels by exploiting channel structure.

Keywords:
data reuseproportionate recursive least squaressparse adaptive equalizationunderwater acoustic communicationℓ1 regularization

Related Experiment Videos

Last Updated: May 14, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
08:30

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

Area of Science:

  • Signal Processing
  • Underwater Communications
  • Adaptive Filtering

Background:

  • Single-carrier underwater acoustic (UWA) communication systems face challenges from sparse multipath channels and long delay spreads.
  • These challenges limit adaptive equalization accuracy and degrade detection performance.

Purpose of the Study:

  • To propose a novel algorithm for sparse adaptive equalization in UWA systems.
  • To improve parameter estimation accuracy and overall communication performance.

Main Methods:

  • Introduced a data reuse (DR) mechanism into the ℓ1-regularized proportionate recursive least-squares (ℓ1-PRLS) framework.
  • Combined proportionate update strategy with ℓ1 sparsity constraint to exploit channel structure.
  • Evaluated performance through numerical simulations comparing DR-ℓ1-PRLS with existing algorithms (LMS, RLS, PRLS, ℓ1-PRLS, DR-PRLS).

Main Results:

  • DR-ℓ1-PRLS demonstrated lower steady-state error compared to other methods.
  • Achieved better bit error rate (BER) performance under sparse UWA channel conditions.
  • Maintained good tracking capability, indicating robustness.

Conclusions:

  • The proposed DR-ℓ1-PRLS algorithm is effective for sparse adaptive equalization in single-carrier UWA communications.
  • The method offers improved accuracy and robustness, outperforming existing algorithms in challenging channel conditions.