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54:41 ASR Lecture 14 ASR Lecture 14	ASR Lecture 14 ASR Lecture 14: Sequence discriminative training speech recognition sequence model probability word likelihood training estimation function hmm lattice mmi statistics topology denominator probabilities network arc bit level lattices From Peter Bell on March 25th, 2021 0 likes 49 plays 0 Licence Type Creative Commons - Attribution Non Commercial Date Created March 4th, 2021
50:22 Mu Niu (University of Glasgow) INTRINSIC GAUSSIAN… Mu Niu (University of Glasgow) INTRINSIC GAUSSIAN PROCESSES ON NONLINEAR MANIFOLDS AND POINT CLOUDS	Mu Niu (University of Glasgow) INTRINSIC GAUSSIAN PROCESSES ON NONLINEAR MANIFOLDS AND POINT CLOUDS 19 February 2021Mu Niu (University of Glasgow) INTRINSIC GAUSSIAN PROCESSES ON NONLINEAR MANIFOLDS AND POINT CLOUDSWe propose a class of intrinsic Gaussian processes (GPs) for interpolation,… statistics research space function kernel manifold gp prediction motion points point distance method manifolds probability heat neighbourhood matrix estimation observation geometry process From OLLIE Quinn on March 1st, 2021 0 likes 17 plays 0 Licence Type All rights reserved Language English Date Created March 19th, 2021
57:46 MLP Interviews - Leonie Bossemeyer MLP Interviews - Leonie Bossemeyer	MLP Interviews - Leonie Bossemeyer Machine Learning Practical interviews - Winter 2020 - Session 2/4. Leonie Bossmeyer is an MSc graduate in Data Science at the University of Edinburgh, and is currently an MSc student in Quantitative… machine learning deep learning copulas density estimation embeddings gan generative adversarial networks normalising flows images image things distribution kind model thing lot bit buildings week damage question variables idea dataset questions flow task label From Pavlos Andreadis on December 7th, 2020 1 likes 38 plays 0 Course Code INFR11132 Licence Type All rights reserved Language English
26:59 Topic 65: Time Averages and Ergodicity (PETARS,… Topic 65: Time Averages and Ergodicity (PETARS, Chapter 8)	Topic 65: Time Averages and Ergodicity (PETARS, Chapter 8) This Topic introduces the notion of estimating statistical averages from a single realisation of a stochastic process. This concept is most easily developed for estimating first and second moments… pgee11164 average process ensemble variance ergodicity realisation infinity sense minus covariance function realisations chapter processes term samples sequence estimator sample estimation From James Hopgood on November 14th, 2020 0 likes 80 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created November 12th, 2020
24:10 Lecture 21 - Capital Cost Estimation I Lecture 21 - Capital Cost Estimation I	Lecture 21 - Capital Cost Estimation I Lecture 21 - Capital Cost Estimation I cost plant costs process capital production estimation capacity reactor distillation industry flow sum portion economics unit gas margin chemical profit From Mennatallah Mohamed Awny Ali Labib on October 31st, 2020 0 likes 110 plays 0 Course Code CHEEE1005 - CHEDSE4 Licence Type All rights reserved The University of Edinburgh Language English
20:15 Topic 50: Linear Least Squares Estimation… Topic 50: Linear Least Squares Estimation (PETARS, Chapter 6)	Topic 50: Linear Least Squares Estimation (PETARS, Chapter 6) The special case of linear least squares is presented as an extremely useful estimation approach, in cases when the signal model can be written as a linear combination of known basis functions, with… pgee11164 times signal linear squares term matrix model estimation vector equations respect form functions function frequency elements expression parameters cost sinusoids From James Hopgood on October 30th, 2020 0 likes 62 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created October 30th, 2020
15:28 Topic 48: Maximum Likelihood Estimation (PETARS,… Topic 48: Maximum Likelihood Estimation (PETARS, Chapter 6)	Topic 48: Maximum Likelihood Estimation (PETARS, Chapter 6) This video introduces the maximum likelihood estimator (MLE) technique as a way of determining a good estimator for a given probabilistic problem. This method is very straightforward and intuitive,… likelihood estimator function variance observations estimation alpha feta parameters method optimization problem fact boundary gradient estimators theta technique parameter theory From James Hopgood on October 26th, 2020 0 likes 76 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created October 26th, 2020
20:20 Topic 43: Measuring Performance of an Estimator… Topic 43: Measuring Performance of an Estimator (PETARS, Chapter 6)	Topic 43: Measuring Performance of an Estimator (PETARS, Chapter 6) In this video, the question of measuring and quantifying the performance of an estimator is discussed. The video focusses on the concepts and definitions of bias and variance of the probability… pgee11164 estimator variance bias function times sample values expectation mu clock hat distribution probability sum n. pdf points parameter estimation summation From James Hopgood on October 22nd, 2020 0 likes 95 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created October 22nd, 2020
18:31 Topic 42: Introduction to Estimation Theory… Topic 42: Introduction to Estimation Theory (PETARS, Chapter 6)	Topic 42: Introduction to Estimation Theory (PETARS, Chapter 6) In this video, Estimation Theory is introduced in which unknown parameters are estimated from data, rather than assuming that problems can be described by fully known distributions or statistics.… pgee11164 observations probability hat estimator sample estimation notation function parameters values histogram distribution parameter variance estimate pdf theory letters variable density From James Hopgood on October 21st, 2020 0 likes 103 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created October 19th, 2020
09:25 Topic 5: Applications of Signal Processing and… Topic 5: Applications of Signal Processing and Communications (PETARS, Chapter 2)	Topic 5: Applications of Signal Processing and Communications (PETARS, Chapter 2) This video considers in more detail some applications of signal processing, including biomedical, surveillance and homeland security, target tracking and navigation, mobile communications, and… pgee11164 network signal processing connection communication analysis imaging communications applications enhancement networks application areas power estimation lecture purpose fi broadband methods From James Hopgood on September 27th, 2020 0 likes 31 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created September 27th, 2020
10:35 Topic 3: Course Guide and Textbooks (PETARS,… Topic 3: Course Guide and Textbooks (PETARS, Chapter 1)	Topic 3: Course Guide and Textbooks (PETARS, Chapter 1) This video outlines the recommended texts for this course, for any students who would like further texts to read beyond the extensive lecture notes. It also recommends other books for further… pgee11164 signal processing websites lecture material textbooks probability resources theory estimation functions notes resource distributions 0s analysis algorithms volume lot library From James Hopgood on September 21st, 2020 0 likes 60 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created September 21st, 2020
13:41 Topic 4: What is Signal Processing? (PETARS,… Topic 4: What is Signal Processing? (PETARS, Chapter 2)	Topic 4: What is Signal Processing? (PETARS, Chapter 2) This video explains the role of signal processing in powering modern communications, entertainment, transportation, and healthcare systems, in addition to numerous industrial and defence… processing signal applications scene sensors device algorithms modalities signals lot machine techniques camera radar senses image computer estimation devices humans From James Hopgood on September 15th, 2020 0 likes 89 plays 0 Course Code PGEE1164 Licence Type All rights reserved Date Created September 15th, 2020
12:12 Topic 2: Course aims and objectives, overview,… Topic 2: Course aims and objectives, overview, key themes (PETARS, Chapter 1)	Topic 2: Course aims and objectives, overview, key themes (PETARS, Chapter 1) This video gives a very brief introduction to signal processing, describes the course aims and objectives from a high-level, the learning outcomes, and prerequisites needed to study the course. The… pgee11164 signal signals processing estimation probability processes functions learning techniques transform linear properties systems fourier prerequisites theory statistics topics frequency variables From James Hopgood on September 5th, 2020 0 likes 29 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created September 5th, 2020
10:54 Topic 11: Motivating Empirical Probability… Topic 11: Motivating Empirical Probability (PETARS, Chapter 3)	Topic 11: Motivating Empirical Probability (PETARS, Chapter 3) This video motivates probability by considering the simplest of problems in the presence of uncertainty. It considers the tools we need to study problems, and the notion of probability. This begins… pgee11164 probability problem taxi definition taxes numbers venice estimation lecture times law frequency answer question signals theory trials increases detection signal From James Hopgood on September 3rd, 2020 0 likes 111 plays 0 Course Code PGEE11164 Licence Type All rights reserved Date Created September 4th, 2020
12:33 Topic 1: How to Study using the Course Materials… Topic 1: How to Study using the Course Materials (PETARS, Chapter 1)	Topic 1: How to Study using the Course Materials (PETARS, Chapter 1) This video welcomes students to the PETARs course, and shows the best way of using the teaching materials to study this course in hybrid teaching mode. The materials available range from handouts… pgee11164 signal probability processing lecture estimation topic handouts theory activities signals topics parts courses credit handout aspects understanding videos variables material From James Hopgood on September 3rd, 2020 0 likes 112 plays 0 Course Code PGEEE11164 Licence Type All rights reserved Date Created September 3rd, 2020
03:56 Evaluation Metrics Evaluation Metrics	Evaluation Metrics Evaluation Metrics - Week 1 predictive analytics micromasters illustrates point estimation performance metric numbers measurement absolute error caption complete statistics average percentage inappropriate positive percentage error scientific method higher picture comparable data analysis overexaggeration observed values outlier statistical terminology reflect generated effects spikes observation data set sensitive accentuation squared error predicted error model statistical deviation and dispersion From Calum Macphail on March 19th, 2019 1 likes 153 plays 0 Course Code PA1.2x Evaluation of Predictive Modelling Licence Type Creative Commons - Attribution Share A Like Language English

Search for tag: "estimation"

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