By Ke-Lin Du,M. N. S. Swamy
Providing a extensive yet in-depth advent to neural community and desktop studying in a statistical framework, this publication offers a unmarried, accomplished source for learn and additional examine. the entire significant renowned neural community types and statistical studying techniques are coated with examples and workouts in each bankruptcy to boost a realistic operating figuring out of the content.
Each of the twenty-five chapters contains state of the art descriptions and demanding study effects at the respective issues. The large assurance contains the multilayer perceptron, the Hopfield community, associative reminiscence types, clustering versions and algorithms, the radial foundation functionality community, recurrent neural networks, significant part research, nonnegative matrix factorization, self sustaining part research, discriminant research, help vector machines, kernel tools, reinforcement studying, probabilistic and Bayesian networks, information fusion and ensemble studying, fuzzy units and good judgment, neurofuzzy versions, implementations, and a few desktop studying subject matters. functions to biometric/bioinformatics and knowledge mining also are included.
Focusing at the well-known accomplishments and their sensible features, educational and technical employees, graduate scholars and researchers will locate that this offers an effective origin and encompassing reference for the fields of neural networks, development attractiveness, sign processing, desktop studying, computational intelligence,
and information mining.
Read or Download Neural Networks and Statistical Learning PDF
Similar pattern recognition programming books
In DetailIn the electronic age of snapshot and video sharing, the necessity for computing device imaginative and prescient is at an all time excessive. have a look round you and you may see that laptop imaginative and prescient is being carried out in every single place. it really is getting used in cars, social networking websites, and in quite a few different fields similar to scientific technology, robotics, protection, domestic automation, etc.
This booklet constitutes the completely refereed post-conference lawsuits of the tenth foreign Workshop on portraits reputation, GREC 2013, held in Bethlehem, PA, united states, in August 2013. The 20 revised complete papers awarded have been conscientiously reviewed and chosen from 32 preliminary submissions. pictures reputation is a subfield of record photograph research that offers with graphical entities in engineering drawings, sketches, maps, architectural plans, musical ratings, mathematical notation, tables, and diagrams.
This e-book constitutes revised chosen papers from the foreign Workshop on scientific Image-Based tactics, CLIP 2013, held along side MICCAI 2012 in Nagoya, Japan, in September 2013. the nineteen papers offered during this quantity have been rigorously reviewed and chosen from 26 submissions. The workshop was once a effective and intriguing discussion board for the dialogue and dissemination of clinically verified, state of the art tools for image-based making plans, tracking and evaluate of scientific strategies.
This e-book, compiles, offers, and explains an important meta-heuristic and evolutionary optimization algorithms whose winning functionality has been confirmed in several fields of engineering, and it contains program of those algorithms to big engineering optimization difficulties. moreover, this booklet publications readers to reviews that experience applied those algorithms by means of delivering a literature evaluate on advancements and purposes of every set of rules.
- Signal Processing for Computer Vision
- Learning OpenCV 3 Application Development
- Pattern Recognition: 9th Mexican Conference, MCPR 2017, Huatulco, Mexico, June 21-24, 2017, Proceedings (Lecture Notes in Computer Science)
- Internet of Things with the Arduino Yún
- Markov Random Field Modeling in Image Analysis (Advances in Computer Vision and Pattern Recognition)
- Computer Vision: From Surfaces to 3D Objects
Additional info for Neural Networks and Statistical Learning
Neural Networks and Statistical Learning by Ke-Lin Du,M. N. S. Swamy