aiParts is a set of C++ classes that can be used to develop artificial intelligence for multi-DECISION problems. It includes classes that implement the High-Hope technique and some sample programs.
標簽： intelligence multi-decisi artificial aiParts
上傳時間： 2017-02-20
上傳用戶：徐孺
Generate random bits, convert to bipolar, corrupt the message by passing through noise and decode using hard DECISION decoding and calculate BER
標簽： Generate bipolar convert corrupt
上傳時間： 2013-12-25
上傳用戶：1966640071
I would like to thank my advisor, Dr. A. Lynn Abbott, for helping me throughout my research, Gary Fleming and the rest of the people at NASA Langley who provided all the flight information and image sequences, and my parents who supported me in my DECISION to enter graduate study. Also, thanks to Phichet Trisirisipal and Xiaojin Gong for helping when I had computer vision questions, and Nathan Herald for his help creating an illustration.
標簽： A. throughout research advisor
上傳時間： 2017-06-18
上傳用戶：maizezhen
Long-TermEvolution(LTE)isarguablyoneofthemostimportantstepsinthecurrentphaseof the development of modern mobile communications. It provides a suitable base for enhanced services due to increased data throughput and lower latency figures, and also gives extra impetus to the modernization of telecom architectures. The DECISION to leave the circuit- switched domainoutofthescope ofLTE/SAEsystem standardization might soundradical but itindicatesthatthetelecomworldisgoingstronglyfortheall-IPconcept----andthedeployment of LTE/SAE is concrete evidence of this global trend.
標簽： Deployment Handbook LTE-SAE The
上傳時間： 2020-06-01
上傳用戶：shancjb
This book is the result of works dedicated to specific applications of metaheuristics in smart electrical grids. From electric transmission, distribution networks to electric microgrids, the notion of intelligence refers to the ability to propose acceptable solutions in an increasingly more restrictive environment. Most often, it refers to DECISION-making assisting tools designed to support all human action.
標簽： Metaheuristics Intelligent Electrical Networks for
上傳時間： 2020-06-07
上傳用戶：shancjb
General paradigm in solving a computer vision problem is to represent a raw image using a more informative vector called feature vector and train a classifier on top of feature vectors collected from training set. From classification perspective, there are several off-the-shelf methods such as gradient boosting, random forest and support vector machines that are able to accurately model nonlinear DECISION boundaries. Hence, solving a computer vision problem mainly depends on the feature extraction algorithm
標簽： Convolutional Networks Neural Guide to
上傳時間： 2020-06-10
上傳用戶：shancjb
Machinelearninghasgreatpotentialforimprovingproducts,processesandresearch.Butcomputers usually do not explain their predictions which is a barrier to the adoption of machine learning. This book is about making machine learning models and their DECISIONs interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as DECISION trees, DECISION rules and linear regression. Later chapters focus on general model- agnosticmethodsforinterpretingblackboxmodelslikefeatureimportanceandaccumulatedlocal effects and explaining individual predictions with Shapley values and LIME.
標簽： interpretable-machine-learning
上傳時間： 2020-06-10
上傳用戶：shancjb
