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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Related Experiment Video

Updated: Dec 3, 2025

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention
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Steered sample algorithm for acoustic source localization.

Bin Liu1,2, Lichao Zhang2, Pengfei Nie1,2

  • 1Shanxi Key Laboratory of Information Survey & Processing, North University of China, Taiyuan, China.

Plos One
|October 26, 2020
PubMed
Summary
This summary is machine-generated.

A new steered sample algorithm (SSA) offers improved acoustic source localization accuracy. This method outperforms the SRP-PHAT, especially with limited array elements and low signal-to-noise ratios (SNR).

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Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • High-precision acoustic source localization relies on effective location methods.
  • Beamforming techniques like steered response power (SRP) offer basic localization but suffer from low spatial resolution.
  • The SRP with phase transform (SRP-PHAT) enhances spatial resolution but can amplify noise and create localization ambiguities.

Purpose of the Study:

  • To propose a novel steered sample algorithm (SSA) for high-precision acoustic source localization.
  • To address the limitations of existing methods, particularly SRP-PHAT, in noisy environments and with limited array configurations.

Main Methods:

  • Development of the steered sample algorithm (SSA) based on the principle of wave propagation reciprocity.
  • Theoretical analysis comparing SSA's localization process to the hyperbolic Radon transform, differentiating it from SRP/SRP-PHAT.
  • Experimental validation of SSA performance against SRP-PHAT using array signal positioning.

Main Results:

  • The SSA demonstrates superior performance in acoustic source localization compared to SRP-PHAT.
  • SSA achieves high precision positioning even with a limited number of array elements.
  • SSA exhibits enhanced performance in scenarios with narrow azimuth signals and lower signal-to-noise ratios (SNR).

Conclusions:

  • The steered sample algorithm (SSA) provides a robust and accurate method for acoustic source localization.
  • SSA overcomes key limitations of SRP-PHAT, offering better precision in challenging acoustic environments.
  • The findings suggest SSA as a promising technique for applications requiring precise localization with sparse arrays and low SNR.