Track Order   | Customer Support   | Request Book   |
International Order
Statistical Signal Processing Volume 1 at Meripustak

Statistical Signal Processing Volume 1

Books from same Author: Steven M Kay

Books from same Publisher: Pearson India

Related Category: Author List / Publisher List

  • Retail Price: ₹ 1020/- [ 5.00% off ]

    Seller Price: ₹ 969

Sold By: T K Pandey      Click for Bulk Order

Offer 1: Get ₹ 111 extra discount on minimum ₹ 500 [Use Code: Bharat]

Offer 2: Get 5.00 % + Flat ₹ 100 discount on shopping of ₹ 1500 [Use Code: IND100]

Offer 3: Get 5.00 % + Flat ₹ 300 discount on shopping of ₹ 5000 [Use Code: MPSTK300]

Free Shipping (for orders above ₹ 499) *T&C apply.

In Stock

Free Shipping Available


Click for International Orders
  • Provide Fastest Delivery
  • 100% Original Guaranteed
    • General Information  
    Author(s)Steven M Kay
    PublisherPearson India
    ISBN9788131728994
    Pages625
    BindingSoftcover
    LanguageEnglish
    Publish YearMay 2020

    Description

    Pearson India Statistical Signal Processing Volume 1 by Steven M Kay

    This book is written on parameter estimation range from highly theoretical to more practical applied statistics. This book strikes a balance between these 2 extremes. Audience is community involved in design and implementation of signal processing algorithms. The primary focus is on obtaining optimal estimation algorithms that may be implemented in a computer. Numerous, worked-out examples. The book is rich in examples that illustrate the theory (of statistical signal processing) and examples that apply the theory to actual signal processing problems of current interest. Features Describes the field of parameter estimation based on time series data. Provides a summary of principal approaches as well as a “roadmap” to use in the selection of an estimator. Extends many of the results for real data/real parameters to complex data/complex parameters. Summarizes as examples many of the important estimators used in practice. Table Of Contents Introduction. Minimum Variance Unbiased Estimation. Cramer-Rao Lower Bound. Linear Models. General Minimum Variance Unbiased Estimation. Best Linear Unbiased Estimators. Maximum Likelihood Estimation. Least Squares. Method of Moments. The Bayesian Philosophy. General Bayesian Estimators. Linear Bayesian Estimators. Kalman Filters. Summary of Estimators.