By Zarubin A.N.
Translated from Differentsialnye Uravneniya, Vol. forty, No. 10, 2004, pp. 1423-1425.
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Writer: Horbach, Ulrich
Affiliation: Harman complicated know-how staff, Northridge, CA, USA
AES conference: 138 (May 2015)
Paper quantity: 9274
Publication Date: might 6, 2015
Traditional headphone measurements be afflicted by huge adaptations if conducted on human matters with probe microphones, and standardized couplers introduce extra biases, as concluded in a contemporary paper. past that, there is not any transparent indication in literature approximately what the particular perceived frequency reaction of a headphone can be. This paper explores new dimension equipment that steer clear of the human physique up to attainable by means of measuring the headphone without delay, in an try to triumph over those regulations and achieve extra accuracy. layout rules are defined within the moment half. a singular, DSP managed prime quality headphone is brought that provides the power to auto-calibrate its frequency reaction to the person who's donning it.
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Extra info for A boundary value problem with an involutive shift in the boundary condition
Sepal W. Petal L. Petal W. 026 attr(,"split_type")  "array" attr(,"split_labels") X1 1 Setosa 2 Versicolor 3 Virginica [ 47 ] Data Manipulation Using plyr Input and arguments The functions in the plyr package accept various input objects: data frames, arrays, and lists. Each input object has its own rule to split the process. In this section, we will discuss input and arguments. The rules of splitting can be described shortly as follows: • Arrays are sliced by dimension into lower dimensional pieces, and the corresponding common function is a*ply(), where the array is the common input and the output can be one among an array, data frame, or list.
Fun argument, the adply() function will just convert the array object into a data frame. frame': 150 obs. : 1 1 1 1 1 1 1 1 1 1 ... 9 ... 1 ... 5 ... 1 ... margins argument works in a similar manner to the apply function in base R. margins argument works correspondingly for higher dimensions, with a combinatorial explosion in the number of possible ways to slice up the array. Comparing default R and plyr In this section, we will compare code side by side to solve the same problem using both default R and plyr.
Table(), we have to specify whether the variable name is present or not using header=TRUE. xlsx. RData format. This file format is convenient to store more than one dataset into a single file. RData file, we can use the load() function. obj" "var1" "var2" "var3" "var4" Note that the objects() command is used to look at all of the objects in the current R session. Now to see the mode and class of each object, we can easily use the mode() and class() function. dta() function. spss(); the output will always be a data frame.