Locus equations and pattern recognition

1998 ◽  
Vol 21 (2) ◽  
pp. 277-277
Author(s):  
Terrance M. Nearey
Keyword(s):  
Pattern Recognition ◽  
Discriminant Analysis ◽  
Quadratic Discriminant Analysis ◽  
Data Set ◽  
Additional Information ◽  
Place Of Articulation ◽  
Second Formant

Although the relations between second formant (F2) onset and F2 vowel are extremely regular and contain important information about place of articulation of the voiced stops, they are not sufficient for its identification. Using quadratic discriminant analysis of a new data set, it is shown that F3 onset and F3 vowel can also contribute substantial additional information to help identify the consonants.

scholarly journals Buildings Cracks Classification Using Zoning and Invariant Moment Features and Quadratic Discriminant Analysis Classifier

2019 ◽  
pp. 158
Author(s):  
I Gede Pasek Suta Wijaya ◽  
Ida Bagus Ketut Widiartha ◽  
Fitri Bimantoro ◽  
Aldian Wahyu Septiadi
Keyword(s):  
Pattern Recognition ◽  
Discriminant Analysis ◽  
Natural Disasters ◽  
Structural Engineering ◽  
Quadratic Discriminant Analysis ◽  
Shape Features ◽  
Invariant Moment ◽  
Building Assessment ◽  
Pattern Recognition Approach ◽  
Moment Features

Natural disasters such as earthquake often cause cracks in buildings and even demolish them. The cracked building must be assessed by an expert to determine whether the building is still suitable for use or not. The feasibility of a building is assessed based on the width, depth, and length of cracks in walls, beams, columns, and even the floor of the building. Only experienced experts can do such kind of task so that building assessment requires many structural engineering experts when an earthquake has happened. However, structural engineering experts are limited which able to do buildings assessment in the area affected. Therefore, the research based on a pattern recognition approach is conducted to classify cracks in buildings to be mild, moderate, or severe. It will be part of automatic building assessment based on the crack analysis. An alternative pattern recognition approach for classifying buildings cracks is a scheme based on zoning and shape features and Quadratic discriminant analysis (QDA) classifier. Based on the experimental results the proposed scheme gives reasonable achievement more than 80% of accuracy.

A Performance Comparison of EMG Classification Methods for Hand and Finger Motion

2014 ◽  
Author(s):  
Sungtae Shin ◽  
Reza Langari ◽  
Reza Tafreshi
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Discriminant Analysis ◽  
Dimension Reduction ◽  
Time Domain ◽  
Classification Accuracy ◽  
Human Motion ◽  
Support Vector ◽  
Classification Methods ◽  
Data Set

For recognizing human motion intent, electromyogram (EMG) based pattern recognition approaches have been studied for many years. A number of methods for classifying EMG patterns have been introduced in the literature. On the purpose of selecting the best performing method for the practical application, this paper compares EMG pattern recognition methods in terms of motion type, feature extraction, dimension reduction, and classification algorithm. Also, for more usability of this research, hand and finger EMG motion data set which had been published online was used. Time-domain, empirical mode decomposition, discrete wavelet transform, and wavelet packet transform were adopted as the feature extraction. Three cases, such as no dimension reduction, principal component analysis (PCA), and linear discriminant analysis (LDA), were compared. Six classification algorithms were also compared: naïve Bayes, k-nearest neighbor, quadratic discriminant analysis, support vector machine, multi-layer perceptron, and extreme machine learning. The performance of each case was estimated by three perspectives: classification accuracy, train time, and test (prediction) time. From the experimental results, the time-domain feature set and LDA were required for the highest classification accuracy. Fast train time and test time are dependent on the classification methods.

Statistical models to identify stand development stages by means of stand characteristics

2011 ◽  
Vol 41 (1) ◽  
pp. 111-123 ◽  
Author(s):  
Markus O. Huber
Keyword(s):  
Discriminant Analysis ◽  
Statistical Models ◽  
Stand Structure ◽  
Multinomial Logistic Regression ◽  
Training Data ◽  
Stand Development ◽  
Quadratic Discriminant Analysis ◽  
Data Set ◽  
Development Stages ◽  
Stand Characteristics

Stand development stages differ mainly in terms of stand structure, stand density, and mortality patterns. As the fulfilment of socio-economic forest functions often depends on stand structure and density, knowledge of the frequency and distribution of stand development stages is needed for optimal forest management. Development stages have been previously identified only qualitatively by experts in forest ecology, but this study developed and compared statistical models to identify development stages by means of stand characteristics. Data from the Austrian National Forest Inventory with 4761 observations of stand development stages were used as the training data set for quadratic discriminant analysis and multinomial logistic regression. The models differ only marginally in terms of the hit ratio and the overall kappa statistic (both determined by means of an independent test data set). The quadratic discriminant analysis has the advantage that the user can reduce or even avoid the influence of the group size on the group-specific model performance by using equal prior probabilities. Furthermore, the discriminant analysis showed the best model behaviour in terms of the explanatory variables and performed best in identifying the stages that were infrequent in the training data set.

Effects of Aging on the Subcortical Encoding of Stop Consonants

2020 ◽  
Vol 29 (3) ◽  
pp. 391-403
Author(s):  
Dania Rishiq ◽  
Ashley Harkrider ◽  
Cary Springer ◽  
Mark Hedrick
Keyword(s):  
Older Adults ◽  
Repeated Measures ◽  
Mixed Model ◽  
Auditory Brainstem ◽  
Auditory Brainstem Responses ◽  
Aging Effects ◽  
Formant Frequency ◽  
Place Of Articulation ◽  
Second Formant ◽  
Effects Of Aging

Purpose The main purpose of this study was to evaluate aging effects on the predominantly subcortical (brainstem) encoding of the second-formant frequency transition, an essential acoustic cue for perceiving place of articulation. Method Synthetic consonant–vowel syllables varying in second-formant onset frequency (i.e., /ba/, /da/, and /ga/ stimuli) were used to elicit speech-evoked auditory brainstem responses (speech-ABRs) in 16 young adults ( M age = 21 years) and 11 older adults ( M age = 59 years). Repeated-measures mixed-model analyses of variance were performed on the latencies and amplitudes of the speech-ABR peaks. Fixed factors were phoneme (repeated measures on three levels: /b/ vs. /d/ vs. /g/) and age (two levels: young vs. older). Results Speech-ABR differences were observed between the two groups (young vs. older adults). Specifically, older listeners showed generalized amplitude reductions for onset and major peaks. Significant Phoneme × Group interactions were not observed. Conclusions Results showed aging effects in speech-ABR amplitudes that may reflect diminished subcortical encoding of consonants in older listeners. These aging effects were not phoneme dependent as observed using the statistical methods of this study.

Application of RTM 3D angle gathers to wide-azimuth data subsalt imaging

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB175-WB182 ◽  
Author(s):  
Yan Huang ◽  
Bing Bai ◽  
Haiyong Quan ◽  
Tony Huang ◽  
Sheng Xu ◽  
...  
Keyword(s):  
Model Updating ◽  
Velocity Model ◽  
Azimuth Angle ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Additional Information ◽  
Time Migration ◽  
Reflection Angle ◽  
Subsalt Imaging

The availability of wide-azimuth data and the use of reverse time migration (RTM) have dramatically increased the capabilities of imaging complex subsalt geology. With these improvements, the current obstacle for creating accurate subsalt images now lies in the velocity model. One of the challenges is to generate common image gathers that take full advantage of the additional information provided by wide-azimuth data and the additional accuracy provided by RTM for velocity model updating. A solution is to generate 3D angle domain common image gathers from RTM, which are indexed by subsurface reflection angle and subsurface azimuth angle. We apply these 3D angle gathers to subsalt tomography with the result that there were improvements in velocity updating with a wide-azimuth data set in the Gulf of Mexico.

A discriminant analysis of high and low-innovative firms: the role of IT, human resources, innovation strategy, intellectual capital and environmental dynamism

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Simona Popa ◽  
Pedro Soto-Acosta ◽  
Daniel Palacios-Marqués
Keyword(s):  
Discriminant Analysis ◽  
Human Resources ◽  
Incremental Innovation ◽  
Organizational Capital ◽  
Data Set ◽  
Content Type ◽  
Innovative Firms ◽  
It Knowledge ◽  
Innovation Outcomes ◽  
Selection Practices

Purpose This paper aims to examine the effect of technological, organizational and environmental factors on the level of innovation outcomes in manufacturing small- and medium-sized enterprises (SMEs). Design/methodology/approach Drawing on the technology-organization-environment theory this paper conducts a discriminant analysis of firms’ innovation level based on a data set of manufacturing SMEs. Findings The results show that low- and high-innovative firms can be distinguished in terms of information technology (IT) knowledge and infrastructure, commitment-based human resources (HR) selection practices, exploitative innovation and organizational capital. Practical implications The study findings support the idea that innovation is a complex phenomenon explained by multiple factors. As a consequence, firms need to devote extra efforts to develop IT knowledge and infrastructure, commitment-based HR selection practices and organizational capital because these are crucial for obtaining greater innovation outcomes. In addition, the identification of exploitative innovation as a strong discriminant variable highlights that the most effective way to be a highly innovative SME is through incremental innovation, which permits the firm to capitalize as much as possible on previous exploratory efforts. Originality/value Although many studies have highlighted that innovation is more challenging for SMEs than for their larger counterparts, the vast majority of studies has been conducted in large companies. This paper extends prior literature by analyzing the discriminant variables that may distinguish between low- and high-innovative manufacturing SMEs.

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