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本文带你探索西班牙美食的魅力,从地道的tapas小吃开始,品尝鲜美章鱼搭配醋蒜酱的独特风味,再到鸡肉卷配塔塔酱的美味享受。西班牙不仅以其激情的弗拉门戈舞蹈和英勇的斗牛士闻名,其地中海美食同样令人难忘。
                            A Taste of Spain

Discover one of the best kept secrets of Mediterranean cuisine



Spain-a land of graceful flamenco dancers and brave bullfighters-has long held a romantic allure for travelers. In face, this Mediterranean country ranks as the world’s second most-visited tourist destinantion. So it seems odd to me that I’ve heard very little about the food of Spain. How does it taste? Is it as delectable as other Mediterranean cuisines? Eager to find out, I visited a local restaurant that serves authentic Spanish meals.

I began my meal with a selection of tapas, which are similar in concept to Hong Kong’s dim sum.

Tapas are enjoyed in the early evening as a snack before a late-night dinner. People in Spain usually order a variety of tapas, served in small portions.The first kind of tapas I tried was fresh octoupus in a vinegar garlic sauce. The chewy texture and pleasantly sour flavor made a delicions treat for the tongue. Hungry for more tapas, I tried a chicken roll served with tartat sauce. A crispy breaded crust surrounded th tender chicken. Dipped in the tangy tartzr sauce, this morsel was a pure delight.

Word bank

Allure (n) 魅力
What is the allure of Paris? Why does it attract so many visitors?
Rank (v)名列
Taipei 101 ranks as the world’s tallest building.
Portion (n) 分量
American restaurants serve larger portions than restaurants in most other countries.
Crust (n) 派皮
The crust on the apple pie was crispy and delicious.

More information
Tartat sauce (n)塔塔酱
Would you like some tartar sauce on your fish?
内容概要:本文围绕“基于数据驱动的 Koopman 算子的递归神经网络模型线性化,用于纳米定位系统的预测控制研究”展开,提出了一种结合Koopman算子理论与递归神经网络(RNN)的数据驱动建模方法,旨在对非线性纳米定位系统进行有效线性化建模,并实现高精度的模型预测控制(MPC)。该方法利用Koopman算子将非线性系统映射到高维线性空间,通过递归神经网络学习系统的动态演化规律,构建可解释性强、计算效率高的线性化模型,进而提升预测控制在复杂不确定性环境下的鲁棒性与跟踪精度。文中给出了完整的Matlab代码实现,涵盖数据预处理、网络训练、模型验证与MPC控制器设计等环节,具有较强的基于数据驱动的 Koopman 算子的递归神经网络模型线性化,用于纳米定位系统的预测控制研究(Matlab代码实现)可复现性和工程应用价值。; 适合人群:具备一定控制理论基础和Matlab编程能力的研究生、科研人员及自动化、精密仪器、机器人等方向的工程技术人员。; 使用场景及目标:①解决高精度纳米定位系统中非线性动态响应带来的控制难题;②实现复杂机电系统的数据驱动建模与预测控制一体化设计;③为非线性系统控制提供一种可替代传统机理建模的有效工具。; 阅读建议:建议结合提供的Matlab代码逐模块分析实现流程,重点关注Koopman观测矩阵构造、RNN网络结构设计与MPC控制器耦合机制,同时可通过替换实际系统数据进行迁移验证,深化对数据驱动控制方法的理解与应用能力。
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