Classification, parameter estimation, and state estimation...

Main
Engineering
Classification, parameter estimation,...

Classification, parameter estimation, and state estimation : an engineering approach using MATLAB

Heijden, Ferdinand van der, Lei, Bangjun, Ming, Feng, Ridder, Dick de, Tax, David M., Xu, Guangzhu, Zou, Yaobing

0 / 0

คุณชอบหนังสือเล่มนี้มากแค่ไหน

คุณภาพของไฟล์เป็นอย่างไรบ้าง

ดาวน์โหลดหนังสือเพื่อประเมินคุณภาพของไฟล์

คุณภาพของไฟล์ที่คุณดาวน์โหลดมาเป็นอย่างไรบ้าง

หมวดหมู่:

ปี:

2017

ฉบับพิมพ์ครั้งที่:

Second edition

สำนักพิมพ์:

John Wiley & Sons

ภาษา:

english

จำนวนหน้า:

467

ISBN 10:

1119152488

ISBN 13:

9781119152484

ไฟล์:

PDF, 11.24 MB

IPFS:

,

english, 2017

อ่านออนไลน์

กำลังแปลงเป็น อยู่

การแปลงเป็น ล้มเหลว

คุณอาจสนใจ

Ferdinand van der Heijden, Robert Duin, Dick de Ridder, David M. J. Tax — Classification, parameter estimation, and state estimation: an engineering approach using MATLAB

James D’Amato — The Ultimate RPG Gameplay Guide: Role-Play the Best Campaign Ever—No Matter the Game!

Jef Aldrich; Jon Taylor — A Dragon Walks into a Bar: 300+ One-Liners, Zingers, and Jokes That Will Slay

Nassim Nicholas Taleb — 动态对冲: 管理普通期权与奇异期权

Ferdinand van der Heijden; Robert P. Duin; Dick de Ridder; David M. J. Tax — Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

Ferdinand van der Heijden — Image Based Measurement Systems: Object Recognition and Parameter Estimation (Design & Measurement in Electronic Engineering)

-- — Adjustment Theory, 2nd Edition

Ulisses Braga-Neto — Fundamentals of Pattern Recognition and Machine Learning, 2nd Edition

Fukunaga K. — Introduction to statistical pattern recognition

Crassidis — Optimal estimation of dynamic systems

Fan, Jianqing; Li, Runze; Zhang, Cun-Hui — Statistical Foundations of Data Science

James V. Candy — Signal Processing The Model Based Approach

Sergios Theodoridis, Konstantinos Koutroumbas — Pattern Recognition, Second Edition

José A. Romagnoli, Mabel Cristina Sanchez — Data Processing and Reconciliation for Chemical Process Operations.

Keinosuke Fukunaga — Introduction to Statistical Pattern Recognition

Maybeck — Stochastic models, estimation and control, Vol.2

Jose A., Romagnoli — Data Processing and Reconciliation for Chemical Process Operations

Theodoridis Koutroumbas — Pattern Recognition

Jerry M. Mendel — Lessons in Estimation Theory for Signal Processing, Communications, and Control (2nd Edition)

Renwick E. Curry — Estimation and Control with Quantized Measurements

Gelb A. — Applied optimal estimation

Renwick E. Curry — Estimation and Control with Quantized Measurements

Ferdinand van der Heijden; Robert P. Duin; Dick de Ridder; David M. J. Tax — Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

Harry L. Van Trees, Kristine L. Bell — Bayesian Bounds for Parameter Estimation and Nonlinear Filtering Tracking

Andrew R. Webb — Statistical pattern recognition

James V. Beck & Kenneth J. Arnold — Parameter Estimation in Engineering and Science

George G. Judge, R. Carter Hill, William E. Griffiths, Helmut Lutkepohl, Tsoung-Chao Lee — Introduction to the Theory and Practice of Econometrics

Yaakov Bar-Shalom, X. Rong Li, Thiagalingam Kirubarajan — Estimation with applications to tracking navigation

C. H Chen — Statistical pattern recognition

Nasser E. Nahi — Estimation Theory and Applications

Bangjun Lei, Guangzhu Xu, Ming Feng, Yaobin Zou, Ferdinand van der Heijden, Dick de Ridder, David M. J. Tax — Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

Jitendra R. Raol, Girija Gopalratnam, Bhekisipho Twala — Nonlinear Filtering: Concepts and Engineering Applications

Ulisses Braga-Neto — Fundamentals of Pattern Recognition and Machine Learning, 2nd

Jürgen Beyerer, Matthias Richter, Matthias Nagel — Pattern recognition: introduction, features, classifiers and principles

Jürgen Beyerer; Matthias Richter; Matthias Nagel — Pattern Recognition: Introduction, Features, Classifiers and Principles

Beyerer, Jürgen, Hagmanns, Raphael, Stadler, Daniel — Pattern Recognition: Introduction, Features, Classifiers and Principles (De Gruyter Textbook)

Christopher M. Bishop, Ilkay Ulusoy (auth.), Joab Winkler, Mahesan Niranjan, Neil Lawrence (eds.) — Deterministic and Statistical Methods in Machine Learning: First International Workshop, Sheffield, UK, September 7-10, 2004. Revised Lectures

H.B. Mitchell — Multi-Sensor Data Fusion: An Introduction

คำที่ถูกค้นหาบ่อยที่สุด