uniform sampling

USAGE SUMMARY

"uniform sampling" is correct and usable in written English.
You can use it to refer to a process where a population is sampled randomly and in equal proportions. For example, "The data was collected using uniform sampling to ensure that the results were representative of the whole population."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

52 human-written examples

Fig. 6 Interpretation of the uniform sampling result in terms of digital filtering associated with LCT.

EURASIP Journal on Advances in Signal Processing

Our proposed voxel-based uniform sampling approach was robust and efficient in almost all tested cases.

EURASIP Journal on Advances in Signal Processing

The voxel-based uniform sampling approach was used to select these points.

EURASIP Journal on Advances in Signal Processing

In this case, discrete uniform sampling changes the orthogonality of bases {ϕ k (t)}.

EURASIP Journal on Advances in Signal Processing

All training, test and validation sets were constructed using random uniform sampling.

Chemistry Central Journal

A 32-element uniform sampling [43] of spherical microphone array is chosen to estimate source locations.

EURASIP Journal on Advances in Signal Processing

Human-verified similar examples from authoritative sources

Similar Expressions

8 human-written examples

Following this vision, a clever way of sampling the signal is the periodic non-uniform sampling.

EURASIP Journal on Advances in Signal Processing

Nested sampling [7] is an non-uniform sampling, using two different samplers in each period.

EURASIP Journal on Advances in Signal Processing

Since log-polar transform uses non-uniform sampling, it becomes very efficient in object recognition.

Human-centric Computing and Information Sciences

They use a feature-based approach based on periodic non-uniform sampling.

EURASIP Journal on Advances in Signal Processing

Hence, time encoding has many similarities to other non-uniform sampling processes.

EURASIP Journal on Advances in Signal Processing

Expert writing Tips

Best practice

When describing your sampling method, be specific about how you achieved "uniform sampling". Mention the criteria used to ensure equal probability of selection.

Common error

Avoid assuming that your sampling is "uniform" without rigorously verifying the selection process. Unequal representation can lead to skewed results and invalidate your analysis.

Linguistic Context

The phrase "uniform sampling" functions primarily as a noun phrase, often acting as the subject or object of a sentence. As stated by Ludwig, it is considered correct and usable in written English. It describes a method or process used in various fields.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Ludwig's WRAP-UP

In summary, "uniform sampling" is a grammatically sound and very common noun phrase, predominantly used in scientific contexts. According to Ludwig, it is correct and suitable for use in written English. It refers to a method ensuring that each member of a population has an equal chance of selection, thereby minimizing bias. While valuable for many research purposes, it may not be ideal for highly diverse populations where certain subgroups require oversampling to ensure adequate representation. Related terms include "random sampling" and "equal probability sampling", though each carries slightly different nuances.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

equal probability sampling

Highlights the equal chance of selection for each element.

unbiased sampling

Focuses on avoiding bias in the selection process.

random sampling

Emphasizes the randomness of selection, without necessarily implying equal probability.

representative sampling

Aims to create a sample that accurately reflects the population.

standardized sampling

A sampling method is implemented consistently across diverse datasets or subgroups.

systematic sampling

Focuses on a structured approach, in contrast to purely random selection.

consistent sampling

Emphasizes the consistency of the sampling methodology

proportional sampling

Sampling proportional to population size.

homogenous sampling

Sampling from a homogeneous population.

stratified sampling

Sampling from predefined subgroups.

FAQs

How is "uniform sampling" used in research?

"Uniform sampling" ensures every member of a population has an equal chance of being selected, preventing bias and ensuring representativeness. This is crucial for accurate data collection and analysis.

What are the advantages of using "uniform sampling"?

The main advantage is reducing bias, leading to more reliable results. It's also relatively simple to implement compared to more complex sampling methods like "stratified sampling".

When might "uniform sampling" not be the best choice?

When dealing with highly diverse populations where certain subgroups are rare. In such cases, "stratified sampling" or "oversampling" might be more appropriate to ensure adequate representation.

What's the difference between "uniform sampling" and "random sampling"?

While both involve random selection, "uniform sampling" specifically emphasizes that each member has an equal probability of selection. "Random sampling" simply means the selection is random, without necessarily guaranteeing equal probabilities.