Seems you have not registered as a member of localhost.saystem.shop!
You may have to register before you can download all our books and magazines, click the sign up button below to create a free account.
Lessons from America
Every war has refugees; every revolution has exiles. Most of the refugees of the French Revolution mourned the demise of the monarchy. Lessons from America examines an unusual group who did not. Doina Pasca Harsanyi looks at the American experience of a group of French liberal aristocrats, early participants in the French Revolution, who took shelter in Philadelphia during the Reign of Terror. The book traces their path from enlightened salons to revolutionary activism to subsequent exile in America and, finally, back to government posts in France—illuminating the ways in which the French experiment in democracy was informed by the American experience.
The Last Libertines
This “rich . . . highly enjoyable portrait of an extraordinary moment in French history” introduces us to 7 dazzling aristocrats who rose and fell during the French Revolution (Guardian). Benedetta Craveri reveals the history of the Libertine generation “whose youth coincided with the French monarchy’s final moment of grace—a moment when . . . a style of life based on privilege and the spirit of caste might acknowledge the widespread demand for change, and . . . reconcile itself with Enlightenment ideals of justice, tolerance, and citizenship.” Here we meet 7 characters who Craveri singles out not only for their “romantic character” but also for “the keenness with which the...
Artificial Neural Networks in Pattern Recognition
This book constitutes the refereed proceedings of the Second IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2006, held in Ulm, Germany in August/September 2006. The 26 revised papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on unsupervised learning, semi-supervised learning, supervised learning, support vector learning, multiple classifier systems, visual object recognition, and data mining in bioinformatics.
Biomimetic Neural Learning for Intelligent Robots
This state-of-the-art survey contains selected papers contributed by researchers in intelligent systems, cognitive robotics, and neuroscience including contributions from the MirrorBot project and from the NeuroBotics Workshop 2004. The research work presented demonstrates significant novel developments in biologically inspired neural models for use in intelligent robot environments and biomimetic cognitive behavior.
Advances in Neurotechnology, Electronics and Informatics
This book is a timely report on current neurotechnology research. It presents a snapshot of the state of the art in the field, discusses current challenges and identifies new directions. The book includes a selection of extended and revised contributions presented at the 2nd International Congress on Neurotechnology, Electronics and Informatics (NEUROTECHNIX 2014), held October 25-26 in Rome, Italy. The chapters are varied: some report on novel theoretical methods for studying neuronal connectivity or neural system behaviour; others report on advanced technologies developed for similar purposes; while further contributions concern new engineering methods and technological tools supporting medical diagnosis and neurorehabilitation. All in all, this book provides graduate students, researchers and practitioners dealing with different aspects of neurotechnologies with a unified view of the field, thus fostering new ideas and research collaborations among groups from different disciplines.
Artificial Neural Networks and Machine Learning – ICANN 2021
The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as model compression, multi-task and multi-label learning, neural network theory, normalization and regularization methods, person re-identification, recurrent neural networks, and reinforcement learning. *The conference was held online 2021 due to the COVID-19 pandemic.
Computational Intelligence
The present book includes a set of selected extended papers from the second International Joint Conference on Computational Intelligence (IJCCI 2010), held in Valencia, Spain, from 24 to 26 October 2010. The conference was composed by three co-located conferences: The International Conference on Fuzzy Computation (ICFC), the International Conference on Evolutionary Computation (ICEC), and the International Conference on Neural Computation (ICNC). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 236 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee,...
From Animals to Animats 16
This book constitutes the refereed proceedings of the 16th International Conference on Simulation of Adaptive Behavior, SAB 2022, held in Cergy-Pontoise, France, in September 2022. The 17 papers presented in this volume were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: Embodiment; Brain-Inspired Control, Adaptation, and Learning; Bio-inspired Vision and navigation; Affective and Social Cognition and Collective Intelligence.
Official Gazette of the United States Patent and Trademark Office
description not available right now.
Sequence Learning
Sequential behavior is essential to intelligence in general and a fundamental part of human activities, ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in many tasks and application fields: planning, reasoning, robotics natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and so on. This book presents coherently integrated chapters by leading authorities and assesses the state of the art in sequence learning by introducing essential models and algorithms and by examining a variety of applications. The book offers topical sections on sequence clustering and learning with Markov models, sequence prediction and recognition with neural networks, sequence discovery with symbolic methods, sequential decision making, biologically inspired sequence learning models.
