xruby 0.3.0 released

XRuby团队宣布发布0.3.0版本,该版本修复了许多bug并显著提高了代码质量。主要改进包括使用注解和代码生成来绑定Java级别方法到Ruby级别方法,更多单元测试通过,以及性能优化。
I am pleased to announce that XRuby 0.3.0 is released:
http://code.google.com/p/xruby/downloads/list

We have fixed lots of bugs and made significant improvement in the code.

Changes from 0.2.1 to 0.3.0:
1. Use annotation and code generation to bind Java level method to Ruby level method (I will talk more about this later).

2. More unit tests passed. We have not eliminated all test failures in test/ruby. But as most of the failures are caused by the implementation of builtin libraries, we will be able to fixed them soon in 0.4.0.

Changes from 0.2.0 to 0.2.1:
1) Dreamhead optimized method/block calls for methods with zero/one
arguments. It makes our performance even better.

2) ZhangYu improved Java integration significantly, he also created a wiki page with lots of good examples:
http://code.google.com/p/xruby/wiki/JavaIntegration

3) Mechiland and I made more ruby unit tests pass.

The most significant change of 0.3.0 is the using of annotation and code generation to bind Java level method to ruby level method. The idea was inspired by the discussions about Java 5 on jruby's maillist, and dreamhead turned it into reality quickly.

As we know, a Ruby method does a little bit more than a Java method. So if we have a method like this in Java:
public class RubyString {
public RubyFloat to_f() {
...
}
}
To turn it (RubyString.to_f) into a Ruby level method, we have to add a few more code to 'wrap' into a class (extends RubyMethod) and 'register' it (defineMethod), e.g:
public class String_to_f extends RubyNoArgMethod {
protected RubyValue run(RubyValue receiver, RubyBlock block) {
return ((RubyString)receiver).to_f();
}
}
...
RubyRuntime.StringClass.defineMethod("to_f", new String_to_f());
For every method, we need to write similar code and it is not fun to repeat yourself. In 0.3.0, we no longer have to do this anymore. As as long as you add annotation like this:
@RubyLevelClass(name="String")
public class RubyString {
@RubyLevelMethod(name="to_f")
public RubyFloat to_f() {
...
}
}
XRuby will turn it into a Ruby level method automatically (using ASM to generate Java bytecode).

I have not used Java 5's annotation feature before, but this looks like an very elegant solution.

Thank everyone who has contributed to this release.
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)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”展开,旨在研究纳米定位系统的预测控制方法。通过结合数据驱动技术与Koopman算子理论,将非线性系统动态近似为高维线性系统,进而利用递归神经网络(RNN)建模并实现系统行为的精确预测。文中详细阐述了模型构建流程、线性化策略及在预测控制中的集成应用,并提供了完整的Matlab代码实现,便于科研人员复现实验、优化算法并拓展至其他精密控制系统。该方法有效提升了纳米级定位系统的控制精度与动态响应性能。; 适合人群:具备自动控制、机器学习或信号处理背景,熟悉Matlab编程,从事精密仪器控制、智能制造或先进控制算法研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①实现非线性动态系统的数据驱动线性化建模;②提升纳米定位平台的轨迹跟踪与预测控制性能;③为高精度控制系统提供可复现的Koopman-RNN融合解决方案; 阅读建议:建议结合Matlab代码逐段理解算法实现细节,重点关注Koopman观测矩阵构造、RNN训练流程与模型预测控制器(MPC)的集成方式,鼓励在实际硬件平台上验证并调整参数以适应具体应用场景。
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