'Gaussian pdf' presentation slideshows

RooFit

RooFit. Introduction Basic functionality Addition and convolution Building multidimensional models Managing data, discrete variables and simultaneous fits More on likelihood calculation and minimization Validation studies. 1. Introduction & Overview. Introduction

2.39k views • 200 slides

Machine Learning: Regression or Classification?

Machine Learning: Regression or Classification?. J.-S. Roger Jang ( ??? ) jang@mirlab.org http://mirlab.org/jang MIR Lab, CSIE Dept. National Taiwan University. GHW Dataset. GHW: Gender-height-weight Source A table of 10000 entries with 3 columns Gender: Categorical Height: Numerical

701 views • 64 slides

Speech Recognition

Speech Recognition. Pattern Classification. Pattern Classification. Introduction Parametric classifiers Semi-parametric classifiers Dimensionality reduction Significance testing. Classifier. Feature Extraction. Class ? i. Feature Vectors x. Observation s. Pattern Classification.

504 views • 50 slides

Presented by, K.L Srinivas (M.Tech 2 nd year) Guided by, Prof. Preeti Rao (Elect. Dept)

CS626-460 : Lecture 34 Pronunciation Scoring For Language Learners Using A Phone Recognition System. Presented by, K.L Srinivas (M.Tech 2 nd year) Guided by, Prof. Preeti Rao (Elect. Dept) Department of Electrical Engineering, IIT Bombay Mumbai , India. Introduction.

544 views • 44 slides

Speech Recognition

Speech Recognition. Pattern Classification. Pattern Classification. Introduction Parametric classifiers Semi-parametric classifiers Dimensionality reduction Significance testing. Classifier. Feature Extraction. Class ? i. Feature Vectors x. Observation s. Pattern Classification.

425 views • 42 slides

Speech Recognition

Speech Recognition. Pattern Classification. Pattern Classification. Introduction Parametric classifiers Semi-parametric classifiers Dimensionality reduction Significance testing. Classifier. Feature Extraction. Class ? i. Feature Vectors x. Observation s. Pattern Classification.

563 views • 40 slides

Speech Recognition

Speech Recognition. Pattern Classification. Pattern Classification. Introduction Parametric classifiers Semi-parametric classifiers Dimensionality reduction Significance testing. Classifier. Feature Extraction. Class ? i. Feature Vectors x. Observation s. Pattern Classification.

420 views • 40 slides

An Introduction to Kalman Filtering by Arthur Pece aecp@diku.dk

An Introduction to Kalman Filtering by Arthur Pece aecp@diku.dk. Generative model for a generic signal. Basic concepts in tracking/filtering. State variables x ; observation y : both are vectors Discrete time: x ( t ), y ( t ), x ( t +1), y ( t +1) Probability P

409 views • 29 slides

460 views • 18 slides

Binomial Probability Distribution

355 views • 11 slides