Ideals, Varieties, and Algorithms

本书深入浅出地介绍了代数几何的核心概念,包括希尔伯特基础定理、诺特尔定理、不变理论、射影几何和维数理论等。通过算法解答一元或多变量多项式方程组的问题,揭示了代数与几何之间的紧密联系。近四十年来,计算方法的复兴推动了理论进步和应用创新,例如在机器人学和几何定理证明中。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

Algebraic Geometry is the study of systems of polynomial equations in one or more variables, asking such questions as: Does the system have finitely many solutions, and if so how can one find them? And if there are infinitely many solutions, how can they be described and manipulated?

The solutions of a system of polynomial equations form a geometric object called a variety; the corresponding algebraic object is an ideal. There is a close relationship between ideals and varieties which reveals the intimate link between algebra and geometry. Written at a level appropriate to undergraduates, this book covers such topics as the Hilbert Basis Theorem, the Nullstellensatz, invariant theory, projective geometry, and dimension theory.

The algorithms to answer questions such as those posed above are an important part of algebraic geometry. Although the algorithmic roots of algebraic geometry are old, it is only in the last forty years that computational methods have regained their earlier prominence. New algorithms, coupled with the power of fast computers, have led to both theoretical advances and interesting applications, for example in robotics and in geometric theorem proving.

今起开看哟!

内容概要:本书《Deep Reinforcement Learning with Guaranteed Performance》探讨了基于李雅普诺夫方法的深度强化学习及其在非线性系统最优控制中的应用。书中提出了一种近似最优自适应控制方法,结合泰勒展开、神经网络、估计器设计及滑模控制思想,解决了不同场景下的跟踪控制问题。该方法不仅保证了性能指标的渐近收敛,还确保了跟踪误差的渐近收敛至零。此外,书中还涉及了执行器饱和、冗余解析等问题,并提出了新的冗余解析方法,验证了所提方法的有效性和优越性。 适合人群:研究生及以上学历的研究人员,特别是从事自适应/最优控制、机器人学和动态神经网络领域的学术界和工业界研究人员。 使用场景及目标:①研究非线性系统的最优控制问题,特别是在存在输入约束和系统动力学的情况下;②解决带有参数不确定性的线性和非线性系统的跟踪控制问题;③探索基于李雅普诺夫方法的深度强化学习在非线性系统控制中的应用;④设计和验证针对冗余机械臂的新型冗余解析方法。 其他说明:本书分为七章,每章内容相对独立,便于读者理解。书中不仅提供了理论分析,还通过实际应用(如欠驱动船舶、冗余机械臂)验证了所提方法的有效性。此外,作者鼓励读者通过仿真和实验进一步验证书中提出的理论和技术。
评论 1
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值