Frequency-weighting functions for broadband speech as estimated by a correlational method

1998 ◽  
Vol 104 (3) ◽  
pp. 1580-1585 ◽  
Author(s):  
Christopher W. Turner ◽  
Bom Jun Kwon ◽  
Chiemi Tanaka ◽  
Jennifer Knapp ◽  
Jodi L. Hubbartt ◽  
...  
Keyword(s):  
Weighting Functions ◽  
Correlational Method ◽  
Frequency Weighting

The problem of frequency weighting functions and standards for birds

2005 ◽  
Vol 118 (3) ◽  
pp. 2018-2018 ◽  
Author(s):  
Robert Dooling ◽  
Elizabeth Brittan‐Powell ◽  
Amanda Lauer ◽  
Micheal Dent ◽  
Isabelle Noirot
Keyword(s):  
Weighting Functions ◽  
Frequency Weighting

scholarly journals UNIFYING ANALYSES OF MULTIPLE RESPONSES.

Dialectologia ◽  
2020 ◽  
Author(s):  
Gotzon AURREKOETXEA ◽  
John NERBONNE ◽  
Jesus RUBIO
Keyword(s):  
Edit Distance ◽  
Multiple Responses ◽  
Weighting Functions ◽  
The Difference ◽  
Frequency Weighting

In dialectology we often encounter irreducible variation in its data, i.e., multiple responses to its probes about the form of a word or phrase. Dialectometry seeks to measure the differences between dialects and has developed several ways to measure the difference between responses when one or both of them is non-unique. We introduce here BILBAO DISTANCE, where the cardinality of response is unimportant, which may be combined with various weighting functions such as edit distance or inverse frequency weighting, and which yields intuitively appealing measures, e.g., when applied to a singleton set {a} and a set with the same element plus a second, yields d({a},{a,b}) = 0.5. It overcomes flaws in earlier proposals and is conceptually simpler and computationally more efficient to apply than earlier measures. We suspect that its results satisfy the metric axioms, as it is certainly symmetric and measures the difference between identical sets as zero.

An H∞ Formulation of Quantitative Feedback Theory

1998 ◽  
Vol 120 (3) ◽  
pp. 305-313 ◽  
Author(s):  
Yongdong Zhao ◽  
Suhada Jayasuriya
Keyword(s):  
Stability Criterion ◽  
Parametric Uncertainty ◽  
Sensitivity Function ◽  
Robust Performance ◽  
Existence Of A Solution ◽  
Weighting Functions ◽  
Performance Constraints ◽  
Small Gain ◽  
Performance Problem ◽  
Frequency Weighting

The QFT robust performance problem in its entirety may be reduced to an H∞ problem by casting each specification as a frequency domain constraint either on the nominal sensitivity function or the complementary sensitivity function. In order to alleviate the conservative nature of a standard H∞ solution that is obtainable for a plant with parametric uncertainty we develop a new stability criterion to replace the small gain condition. With this new stability criterion it is shown that the existence of a solution to the standard H∞ problem guarantees a solution to the QFT problem. Specifically, we provide an explicit characterization of necessary frequency weighting functions for an H∞ embedding of the QFT specifications. Due to the transparency in selecting the weighting functions, the robust performance constraints can be easily relaxed, if needed, for the purpose of assuring a solution to the H∞ problem. Since this formulation provides only a sufficient condition for the existence of a QFT controller one can then use the resulting H∞ compensator to initiate the QFT loop shaping step.

Hubungan Kepribadian dan Lingkungan dengan Kemampuan Bahasa Indonesia

2019 ◽  
Vol 2 ◽  
Author(s):  
Imam Mujtaba ◽  
Yufiarti Yufiarti ◽  
Elindra Yetti
Keyword(s):  
Research Method ◽  
Positive Relationship ◽  
Language Ability ◽  
Descriptive Statistics ◽  
Quantitative Approach ◽  
Assessment Scale ◽  
Correlation Technique ◽  
Correlational Method ◽  
The Relationship ◽  
Bahasa Indonesia

The purpose of this study was to determine the relationship between students’ personality and environment with their Indonesian Language ability. This research was conducted in South Tangerang City involving 392 2nd grade students. This research method used correlational method with quantitative approach by using descriptive statistics. Data was collected using an assessment scale instrument and analyzed by using correlation technique (regression). The results of this study showed that: (1) There was a positive relationship between personality and students’ Indonesian Language ability with a significant level of α = 0.05, obtained tcal 8.77 ˃ ttable 1.97. (2) There wasa positive relationship between the environment and the students’ Indonesian Language ability with a significant level of α = 0.05, which obtained 9.03 ˃ t table 1.97. (3) There was a positive relationship between personality and environment with the students’ Indonesian Language ability; with a significant level of α = 0.05, obtained tcal 7.92 ˃ t table 1.97. The Implications of the study identified that Indonesian Language ability of the students can be influenced by their personality and environment.

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