sampling

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sampling

the selection of part of a total population of consumers or products whose behaviour or performance can be analysed, in order to make inferences about the behaviour or performance of the total population, without the difficulty and expense of undertaking a complete census of the whole population.

Samples may be chosen randomly, with every consumer or product in the population having an equal chance of being included. Random samples are most commonly used by firms in QUALITY CONTROL where they are used as a basis for selecting products, components or materials for quality testing.

Alternatively, samples may be chosen by dividing up the total population into a number of distinct sub-groups or strata, then selecting a proportionate number of consumers or products from each sub-group since this is quicker and cheaper than random sampling. In MARKETING RESEARCH and opinion polling, quota sampling is usually employed where interviewers select the particular consumers to be interviewed, choosing the numbers of these consumers in proportion to their occurrence in the total population.

Samples may be:

  1. cross-sectional, where sample observations are collected at a particular point in time, for example data on company sales and the incomes of consumers in the current year, embracing a wide range of different income groups, as a basis for investigating the relationship between sales and income;
  2. longitudinal, where sample observations are collected over a number of time periods, for example data on changes in company sales over a number of years and changes in consumer incomes over the same time periods, as a basis for investigating the relationship between sales and income. See STATISTICAL INFERENCES, QUESTIONNAIRE.
Collins Dictionary of Business, 3rd ed. © 2002, 2005 C Pass, B Lowes, A Pendleton, L Chadwick, D O’Reilly and M Afferson
References in periodicals archive ?
Lenna Barbara Peppers Goldhill Mandrill S = 0.1 Sparse representation MH-SPL 25.12 21.05 24.41 24.07 19.23 NESTA 21.14 18.90 20.25 21.11 18.04 Quantization DPCM + NESTA 21.14 18.90 20.25 21.11 18.04 Proposed 21.04 19.13 20.90 21.14 18.07 S = 0.3 Sparse representation MH-SPL 29.89 24.91 30.08 28.19 21.54 NESTA 27.28 22.99 26.86 26.32 20.46 Quantization DPCM + NESTA 27.28 22.99 26.86 26.32 20.46 Proposed 33.32 27.92 32.69 30.51 23.67 S = 0.5 Sparse representation MH-SPL 32.93 27.74 33.21 30.72 23.50 NESTA 30.83 25.52 31.16 29.63 22.77 Quantization DPCM + NESTA 30.83 25.52 31.16 29.63 22.77 Proposed 37.79 32.49 36.40 34.61 27.79 Table 2: Comparison of execution time(s) to reconstruct an image when using different algorithms.
Experience shows that in a continuous-tone image, the DC coefficients of adjacent blocks are close, so we encode the DC coefficients using DPCM. It outputs the first coefficient, followed by differences of the DC coefficients of consecutive blocks.
McGee, "Joseph James Roswell and Alice Reynolds Flower:, DPCM, pp.311-13.
DPCM differential PCM (pulse code modulation): transmit value differences
Jayant, "Subsampling of a DPCM Speech Channel to Provide Two "Self-Contained" Half-Rate Channels," Bell Labs Technical Journal, vol.
One effective way to use the correlation between samples within a frame is studied in [19], where the analysis is done for high speech signal quality by employing DPCM scheme with the switched first-order predictor.
Predict 40% BTC 6% DCT 45% DWT 10% Lossless JEGP 6% Rice 10% DPCM 19% JPEG-LS 4% Note: Table made from pie chart.
It is a hybrid of DCT (Discrete Cosine Transform) and DPCM (Differential Pulse Code Modulation) schemes with motion estimation [6, 8].
For each block, the DC coefficient is performed a differential pulse code modulation (DPCM).The 63 coefficients are first converted into a 1-D zig-zag sequence, and then are conducted entropy encoding.
Differential pulse code modulation (DPCM) is one of the most effective techniques for signal processing and transmission widely used in telecommunications, speech [1], [2] and image coding [3], [4], and medical research [5]-[7].
Diffeential pulse code modulation (DPCM) [11] is a source coding scheme that was developed for encoding sources with memory.