Making machines with brains

本文讲述了计算机先驱艾伦·图灵的故事。孤独童年使他对人脑工作原理感兴趣,立志制造像人一样“聪明”的机器。他毕业后画出类似打字机的机器并写报告,虽当时少有人理解,但二战时他借此设计出能高速破译纳粹密码的早期计算机类机器。

Making machines with brains

By 21ST
Published on 2001-10-15
Posted on 2002-07-01 00:00:00


孤独的童年让图灵对人脑工作原理产生兴趣,他立志制造出一种能像人一样"聪明"的机器。你知道计算机背后的故事吗?

WHAT is the "cleverest" machine in history? If you're anything like nine out of ten people in the world, you'll say it's a computer, a machine with mathematical logic (数学逻辑) that can reason in the same way as humans.

Alan Mathison Turing never expected to be the father of a machine with such a title.

He was born in London in 1912, the second of his parents' two sons. His parents worked in India while Turing and his brother spent their childhoods in Britain.

Turing's loneliness during this time may have led to his lifelong interest in how the human mind works. He believed that the mind creates its own world when the real world is not acceptable to it. At 13, he already showed a talent for mathematics. He wasn't perfect though. His teachers said his work was hard to read.

After graduating from Cambridge University, he remained there as a teacher. At that time, his interest in the human mind led him to draw a machine.

He described it as a typewriter-like device. It could read instructions (指令) that were placed in code on a special tape. The machine moved from one tape to the next - responding to commands and changing its responses to do whatever it was told to do.

In 1937, Turing wrote a report about his machine. However, few people understood what he was talking about.

Even fewer would have predicted (预测) that Turing's machine would finally become one of the greatest inventions of the century.

But the report changed Turing's whole life. After the start of World War II, the British Government ordered him to serve in a special department. The task of all those working there was to break codes used by the Nazis ().

Turing's talent shone in this top secret work. He played a major role in designing an early computer-like machine that could decipher (破译) Nazi codes at high speed.

HELP
If you're anything like nine out of ten people in the world: 如果你同大多数人一样
reason v. 推理
show a talent for: 显示在...方面的才能
respond to command: 对命令做出反应
a rosy future: 光明的前景
After the war, he returned to Cambridge, hoping to return to his life as a teacher. But he was offered the chance to build a machine based on his ideas from 1937.

After building his machine, he continued to write and to think. He saw a rosy future for what was now becoming known as the computer. But other parts of his life were very unhappy. On June 7, 1954, he killed himself.
本课题设计了一种利用Matlab平台开发的植物叶片健康状态识别方案,重点融合了色彩与纹理双重特征以实现对叶片病害的自动化判别。该系统构建了直观的图形操作界面,便于用户提交叶片影像并快速获得分析结论。Matlab作为具备高效数值计算与数据处理能力的工具,在图像分析与模式分类领域应用广泛,本项目正是借助其功能解决农业病害监测的实际问题。 在色彩特征分析方面,叶片影像的颜色分布常与其生理状态密切相关。通常,健康的叶片呈现绿色,而出现黄化、褐变等异常色彩往往指示病害或虫害的发生。Matlab提供了一系列图像处理函数,例如可通过色彩空间转换与直方图统计来量化颜色属性。通过计算各颜色通道的统计参数(如均值、标准差及主成分等),能够提取具有判别力的色彩特征,从而为不同病害类别的区分提供依据。 纹理特征则用于描述叶片表面的微观结构与形态变化,如病斑、皱缩或裂纹等。Matlab中的灰度共生矩阵计算函数可用于提取对比度、均匀性、相关性等纹理指标。此外,局部二值模式与Gabor滤波等方法也能从多尺度刻画纹理细节,进一步增强病害识别的鲁棒性。 系统的人机交互界面基于Matlab的图形用户界面开发环境实现。用户可通过该界面上传待检图像,系统将自动执行图像预处理、特征抽取与分类判断。采用的分类模型包括支持向量机、决策树等机器学习方法,通过对已标注样本的训练,模型能够依据新图像的特征向量预测其所属的病害类别。 此类课题设计有助于深化对Matlab编程、图像处理技术与模式识别原理的理解。通过完整实现从特征提取到分类决策的流程,学生能够将理论知识与实际应用相结合,提升解决复杂工程问题的能力。总体而言,该叶片病害检测系统涵盖了图像分析、特征融合、分类算法及界面开发等多个技术环节,为学习与掌握基于Matlab的智能检测技术提供了综合性实践案例。 资源来源于网络分享,仅用于学习交流使用,请勿用于商业,如有侵权请联系我删除!
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