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Fundamental Of Statistical Signal Processing Vol 1 | By Steven M. Kay | Latest Edition | Pearson Publication ( English Medium )
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| 745-970 |
[Shipping Cost = Standard Mode, Expedite Mode]
Fundamental Of Statistical Signal Processing Vol 1 | By Steven M. Kay | Latest Edition | Pearson Publication ( English Medium ).
🔍 Book Description
"Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory" by Steven M. Kay is a globally respected and widely adopted textbook that introduces and explains the principles of statistical estimation theory. It serves as a foundational text for graduate-level students and professionals in signal processing, communications, control systems, radar, sonar, navigation, and machine learning.
The book emphasizes parameter estimation from observed signals contaminated by noise, providing theoretical depth along with practical applications. It covers important estimation methods such as Maximum Likelihood (ML), Bayesian Estimation, Least Squares (LS), Minimum Variance Unbiased Estimators (MVUE), and Kalman Filtering. The text builds intuition while maintaining mathematical rigor, reinforced with worked-out examples, numerical problems, and conceptual exercises.
✨ Key Features
Comprehensive Coverage of Estimation Theory – Includes all key techniques like MVUE, ML, LS, Bayesian, and Method of Moments.
Real-World Applications – Examples and exercises designed for use in communications, radar, and signal processing fields.
Unified Treatment – Presents Wiener and Kalman filters within a unified framework.
Mathematically Rigorous Yet Accessible – Balances theory with accessibility for students with a background in probability and linear algebra.
Extensive Problem Sets – Contains over 230 problems and 100+ worked examples to test conceptual clarity.
Performance Bounds – Includes topics like the Cramér-Rao Lower Bound and Fisher Information Matrix.
Support for Complex Data – Addresses estimation problems involving complex-valued signals.
Structured Pedagogy – Each chapter is logically organized with summaries and key takeaways.
Timeless Utility – Remains the standard reference in statistical signal processing even decades after first publication.
Perfect for Graduate Studies – Used in leading universities and research institutions worldwide.
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Product Details
| SKU / BOOK Code: | Prsn-Fundmntl-Of-Sgnl-Prcsng-(E) |
| Publisher: | Pearson Publication |
| Author: | Steven M. Kay |
| Binding Type: | Paperback |
| No. of Pages: | 595 |
| ISBN-10: | 8131728994 |
| ISBN-13: | 978-8131728994 |
| Edition: | Latest Edition |
| Language: | English Medium |
| Publish Year: | 2025-06 |
| Weight (g): | 2600 |
| Product Condition: | New |
| Reading Age: | Above 10 Years |
| Country of Origin: | India |
| Genre: | Textbooks & Study Guides |
| Manufacturer: | Pearson Publication |
| Importer: | Pearson Publication |
| Packer: | Fullfilled by Supplier |
Product Description
Fundamental Of Statistical Signal Processing Vol 1 | By Steven M. Kay | Latest Edition | Pearson Publication ( English Medium ).
🔍 Book Description
"Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory" by Steven M. Kay is a globally respected and widely adopted textbook that introduces and explains the principles of statistical estimation theory. It serves as a foundational text for graduate-level students and professionals in signal processing, communications, control systems, radar, sonar, navigation, and machine learning.
The book emphasizes parameter estimation from observed signals contaminated by noise, providing theoretical depth along with practical applications. It covers important estimation methods such as Maximum Likelihood (ML), Bayesian Estimation, Least Squares (LS), Minimum Variance Unbiased Estimators (MVUE), and Kalman Filtering. The text builds intuition while maintaining mathematical rigor, reinforced with worked-out examples, numerical problems, and conceptual exercises.
✨ Key Features
Comprehensive Coverage of Estimation Theory – Includes all key techniques like MVUE, ML, LS, Bayesian, and Method of Moments.
Real-World Applications – Examples and exercises designed for use in communications, radar, and signal processing fields.
Unified Treatment – Presents Wiener and Kalman filters within a unified framework.
Mathematically Rigorous Yet Accessible – Balances theory with accessibility for students with a background in probability and linear algebra.
Extensive Problem Sets – Contains over 230 problems and 100+ worked examples to test conceptual clarity.
Performance Bounds – Includes topics like the Cramér-Rao Lower Bound and Fisher Information Matrix.
Support for Complex Data – Addresses estimation problems involving complex-valued signals.
Structured Pedagogy – Each chapter is logically organized with summaries and key takeaways.
Timeless Utility – Remains the standard reference in statistical signal processing even decades after first publication.
Perfect for Graduate Studies – Used in leading universities and research institutions worldwide.
Search Key - Fundamentals of Statistical Signal Processing Volume 1 Kay, , Steven M. Kay estimation theory book, , Statistical Signal Processing Kay Pearson, , Estimation theory Steven Kay textbook, , Signal processing estimation theory volume 1, , Pearson Kay signal processing latest edition, , Estimation theory graduate level book, , Kalman filter fundamentals Steven Kay, , Maximum likelihood estimation Steven Kay, , Bayesian estimation statistical signal processing, , Least squares estimation Kay volume 1, , Cramer Rao bound Steven Kay, , Statistical estimation theory textbook, , Steven M. Kay signal processing reference, , Parameter estimation signal processing Kay, , Wiener filter estimation Steven Kay, , Advanced signal processing estimation book, , Method of moments Steven Kay, , MVUE estimation theory Kay, , Complex signal estimation Steven Kay, , Estimation theory for engineers Kay, , Signal processing with noise estimation Kay, , Statistical tools in signal processing Kay, , Estimation techniques in signal processing, , Time series estimation Kay book, , Detection and estimation theory Kay, , Signal parameter estimation textbook, , Estimation theory examples Steven Kay, , Kalman filter and Bayesian methods Kay, , Best book for signal estimation theory.
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Selling Price & Shipping Fee: In Product details page we have clearly mentioned the Selling Price & Shipping Fees separately, So, when you click on "BUY NOW" You will be charges Selling Price + Shipping Fees. The Shipping fees may different for each products depends on the weight of the Product. The shipping cost includes the courier charges, packaging charges, transport charges, fuel charges and other charges. Sometimes the total payable amount may be different for Instamojo Payment Gateway. Buyers are requested to check before purchasing the products. After making the purchase we may not allow or consider users to modify.
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Generally the courier partner support delivery during business hours (9:00 - 20:00) Mon - Sat: Fedex, Trackon, Gati, Delhivery, Indian Post.
The actual delivery time may differ from the given Estimated timeline. For more information on delivery time and shipping charges, please refer to our dedicated support team through ECG Portal.
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