Pattern-MAC (PMAC) protocol, instead of having fixed sleepwakeups, the sleep-wakeup schedules of the sensor nodes are adaptively determined. The schedules are decided based on a node’s own traffic and that of its neighbors.
標簽： sleepwakeups sleep-wakeup Pattern-MAC schedules
上傳時間： 2017-08-28
上傳用戶：cainaifa
模式識別與智能系統 Pattern Recognition and Intelligent System
標簽： Intelligent Recognition Pattern System
上傳時間： 2017-09-01
上傳用戶：dapangxie
This is a MATLAB program for Histogram Matching. Used In digital Image Processing.
標簽： Processing Histogram Matching digital
上傳時間： 2013-12-24
上傳用戶：xiaoxiang
It can be used to matching the patterns
標簽： matching patterns used can
上傳時間： 2013-12-17
上傳用戶：TF2015
local binary pattern matlab source code
標簽： pattern binary matlab source
上傳時間： 2017-09-05
上傳用戶：daoxiang126
Pattern Analysis is the process of fi nding general relations in a set of data, and forms the core of many disciplines, from neural networks to so-called syn- tactical pattern recognition, from statistical pattern recognition to machine learning and data mining. Applications of pattern analysis range from bioin- formatics to document retrieval.
標簽： the relations Analysis Pattern
上傳時間： 2017-09-07
上傳用戶：SimonQQ
this is for radiation pattern for dipole
標簽： for radiation pattern dipole
上傳時間： 2017-09-09
上傳用戶：奇奇奔奔
A Multimodal Pattern Recognition Framework for Speaker Detection
標簽： Recognition Multimodal Framework Detection
上傳時間： 2013-11-26
上傳用戶：caozhizhi
To describe Pattern Recognition using Machine Learning Method. It is good for one who want to learn machine learning.
標簽： Pattern recognition ML machine learning
上傳時間： 2016-04-14
上傳用戶：shishi
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propa- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications.
標簽： Bishop-Pattern-Recognition-and-Ma chine-Learning
上傳時間： 2020-06-10
上傳用戶：shancjb
