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Books on the topic 'Sampling – Software'

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Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

McGuire, Sam. Audio sampling: A practical guide. Amsterdam: Focal Press, 2008.

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2

Venosa, Elettra. Software radio: Sampling rate selection, design and synchronization. New York: Springer Verlag, 2012.

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3

Music technology and the project studio: Sampling and synthesis. New York: Routledge, 2012.

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4

McGuire, Sam. Software sampling: A step-by-step guide to creating your own sampled instruments. Burlington, MA: Focal Press, 2008.

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5

Sparks, Anita. Sediment sampling application: User instructions : R:Base version 1.2. [Olympia, Wash.]: Northwest Indian Fisheries Commission, 1994.

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6

Classical and adaptive clinical trial designs with ExpDesign Studio? Hoboken, N.J: John Wiley, 2008.

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7

Adaptive design theory and implementation using SAS and R. Boca Raton: CRC Press, 2014.

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8

Chang, Mark. Adaptive design theory and implementation using SAS and R. Boca Raton, FL: CRC Press, 2007.

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9

Adaptive design theory and implementation using SAS and R. Boca Raton: Taylor & Francis, 2008.

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10

Sampling and Soft Synth Power! Thomson Course Technology, 2005.

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11

Audio Sampling: A Practical Guide. Focal Press, 2007.

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12

Venosa, Elettra, fredric j. harris, and Francesco A. N. Palmieri. Software Radio: Sampling Rate Selection, Design and Synchronization. Springer, 2013.

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13

Venosa, Elettra, fredric j. harris, and Francesco A. N. Palmieri. Software Radio: Sampling Rate Selection, Design and Synchronization. Springer, 2011.

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14

Arkin, Herbert. Statistical Sampling Software Package: IBM Version: PC (128K)(Disk). McGraw-Hill Software, 1985.

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15

Jean, Bate Lisa, and Pacific Northwest Research Station (Portland, Or.), eds. Log sampling methods and software for stand and landscape analyses. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2008.

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16

Jean, Bate Lisa, and Pacific Northwest Research Station (Portland, Or.), eds. Log sampling methods and software for stand and landscape analyses. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2008.

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17

Jean, Bate Lisa, and Pacific Northwest Research Station (Portland, Or.), eds. Log sampling methods and software for stand and landscape analyses. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2008.

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18

Log sampling methods and software for stand and landscape analyses. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2008.

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19

Brink, G. E. ONEPHASE: a simulation program to commpare 1-phase sampling strategies. 1992.

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20

Sample Rate Conversion in Software Configurable Radios (Artech House Mobile Communications Series). Artech House Publishers, 2002.

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21

Miksza, Peter, and Kenneth Elpus. Analyses of Data from Complex Survey Sampling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199391905.003.0011.

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This chapter introduces the specialized techniques necessary for analyzing data that have been gathered in a complex or multistage survey sample. The chapter details the methods most commonly used to collect complex survey data and then explains the specific statistical tools that must be employed to correctly analyze complex survey data. First, an overview of the various types of sampling methods is presented, beginning with simple random sampling and moving through other methods to finally discuss the commonly employed research techniques of cluster sampling. The chapter continues with a discussion of survey weights—what they mean and how they are derived. The chapter concludes with software-based suggestions on the proper analysis of survey data.

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22

Rajan, Gupta, and Langley Research Center, eds. Estimating residual fault hitting rates by recapture sampling: Final report for the period ending December 31, 1988. Norfolk, Va: Old Dominion University Research Foundation, 1988.

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23

WILEY. Software Samplings - A New Spin on Software CD. John Wiley & Sons Inc, 1998.

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24

Taberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. Environmental DNA for functional diversity. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0010.

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Chapter 10 “Environmental DNA for functional diversity” discusses the potential of environmental DNA to assess functional diversity. It first focuses on DNA metabarcoding and discusses the extent to which this approach can be used and/or optimized to retrieve meaningful information on the functions of the target community. This knowledge usually involves coarsely defined functional groups (e.g., woody, leguminous, graminoid plants; shredders or decomposer soil organisms; pathogenicity or decomposition role of certain microorganisms). Chapter 10 then introduces metagenomics and metatranscriptomics approaches, their advantages, but also the challenges and solutions to appropriately sampling, sequencing these complex DNA/RNA populations. Chapter 10 finally presents several strategies and software to analyze metagenomes/metatranscriptomes, and discusses their pros and cons.

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25

Bisseling, Rob H. Parallel Scientific Computation. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198788348.001.0001.

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This book explains how to use the bulk synchronous parallel (BSP) model to design and implement parallel algorithms in the areas of scientific computing and big data. Furthermore, it presents a hybrid BSP approach towards new hardware developments such as hierarchical architectures with both shared and distributed memory. The book provides a full treatment of core problems in scientific computing and big data, starting from a high-level problem description, via a sequential solution algorithm to a parallel solution algorithm and an actual parallel program written in the communication library BSPlib. Numerical experiments are presented for parallel programs on modern parallel computers ranging from desktop computers to massively parallel supercomputers. The introductory chapter of the book gives a complete overview of BSPlib, so that the reader already at an early stage is able to write his/her own parallel programs. Furthermore, it treats BSP benchmarking and parallel sorting by regular sampling. The next three chapters treat basic numerical linear algebra problems such as linear system solving by LU decomposition, sparse matrix-vector multiplication (SpMV), and the fast Fourier transform (FFT). The final chapter explores parallel algorithms for big data problems such as graph matching. The book is accompanied by a software package BSPedupack, freely available online from the author’s homepage, which contains all programs of the book and a set of test programs.

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