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Related Concept Videos

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used.
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
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...

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Related Experiment Video

Updated: May 27, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

A new adaptive line enhancer based on singular spectrum analysis.

Saeid Sanei1, Tracey K M Lee, Vahid Abolghasemi

  • 1Department of Computing, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH, UK. s.sanei@surrey.ac.uk

IEEE Transactions on Bio-Medical Engineering
|November 4, 2011
PubMed
Summary
This summary is machine-generated.

A novel adaptive line enhancer (ALE) using singular spectrum analysis (SSA) improves denoising of periodic signals. This method effectively separates biomedical data like EMG from ECG artifacts, even with non-Gaussian noise.

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Area of Science:

  • Signal Processing
  • Biomedical Engineering
  • Data Analysis

Background:

  • Traditional adaptive line enhancers (ALE) primarily denoise periodic signals corrupted by white noise.
  • ALE's effectiveness is limited by its reliance on second-order statistics and suitability for narrowband signals.

Purpose of the Study:

  • To introduce a new adaptive line enhancer (ALE) based on singular spectrum analysis (SSA).
  • To enhance the denoising capabilities for periodic signals, particularly in biomedical applications.

Main Methods:

  • The proposed method integrates SSA with adaptive filtering during the reconstruction phase.
  • Eigentriples are adaptively selected using a delayed version of the data.
  • Exploits the full eigen-spectrum of the embedding matrix, moving beyond second-order statistics.

Main Results:

  • The new ALE demonstrates effectiveness for non-Gaussian noise and wideband periodic signals.
  • Experiments on synthetic data show superior performance in separating biomedical signals.
  • Successfully demonstrated separation of electromyography (EMG) signals contaminated by electrocardiography (ECG) artifacts.

Conclusions:

  • The SSA-based ALE offers a robust solution for denoising complex biomedical signals with periodic components.
  • This advanced technique broadens the applicability of ALE to a wider range of noise types and signal bandwidths.