jslu + math   81

Introduction to Signal Processing: Table of Contents
A Pragmatic Introduction to Signal Processing, with applications in scientific measurement
@CourseOutline  @Concept  @Example  Math  Engineering  Tutorial 
19 days ago by jslu
臺大開放式課程 (NTU OpenCourseWare)
為促進教學資源共享,落實建構終身學習環境理念,提供自學者更寬廣的學習內容,開放式課程(OCW)已蔚為世界風潮。而本校為響應全球開放式教育運動並善盡社會責任、提高本校能見度,將邀請各學系提供能彰顯該系特色之優質課程,建置「開放式課程」網站。其教材內容除提供社會人士免費上網自我學習外,並提供予國內外學生、教師及相關研究人員作為學習輔助、課程教學及研究題材之參考,以提昇學習效果及研究品質。
@Project  @CourseOutline  Literature  Science  FreeOfCharge  Tutorial  Law  Art  History  Politics  Sociology  Math  Engineering 
march 2019 by jslu
[1807.08416] Some Fundamental Theorems in Mathematics
An expository hitchhikers guide to some theorems in mathematics. - History and Overview
@Download  @Research  Math  History 
january 2019 by jslu
The Scientist & Engineer's Guide to Digital Signal Processing, 1999 | Education | Analog Devices
This book provides a practical introduction to Digital Signal Processing. Covering a wide range of topics, including linear systems, discrete fourier transforms, fast fourier transforms, digital filters, this book is an ideal introductory text for those new to DSP, and an excellent reference for more experienced users.
@Download  @eBook  @Concept  @Example  DigitalSignalProcessing  Math  Engineering  Tutorial 
january 2019 by jslu
Why is Maxwell's Theory so hard to understand?
The modern view of the world that emerged from Maxwell's theory is a world with two layers. The first layer, the layer of the fundamental constituents of the world, consists of fields satisfying simple linear equations. The second layer, the layer of the things that we can directly touch and measure, consists of mechanical stresses and energies and forces. The two layers are connected, because the quantities in the second layer are quadratic or bilinear combinations of the quantities in the first layer. To calculate energies or stresses, you take the square of the electric field-strength or multiply one component of the field by another. The two-layer structure of the world is the basic reason why Maxwell's theory seemed mysterious and difficult. The objects on the first layer, the objects that are truly fundamental, are abstractions not directly accessible to our senses. The objects that we can feel and touch are on the second layer, and their behaviour is only determined indirectly by the equations that operate on the first layer. The two-layer structure of the world implies that the basic processes of nature are hidden from our view.
@Article  @Research  Math  WorldView 
january 2019 by jslu
Seeing Theory - A visual introduction to probability and statistics
Seeing Theory was created by Daniel Kunin while an undergraduate at Brown University. The goal of this website is to make statistics more accessible through interactive visualizations
@Site  @Project  @Concept  @CourseOutline  Math  Problem-solving  InterpersonalCommunication  MeaningManagement  UnexpectednessUncertaintyAndImpermanence  Tutorial 
december 2018 by jslu
B.S. in Artificial Intelligence - Curriculum | Carnegie Mellon School of Computer Science
BSAI majors will take courses in math and statistics, computer science, AI, science and engineering, and humanities and arts. There's also room built into the curriculum for academic exploration via electives. Here's how the curriculum breaks down.
@CourseOutline  @Reference  AI  MachineLearning  Math  Interdisciplinarity  Engineering 
september 2018 by jslu
A First Course in Differential Equations for Scientists and Engineers
These are notes for an introductory one semester course in differential equations originally compiled for Summers 2014-18.
@CourseOutline  Math  Tutorial 
september 2018 by jslu
Foundations of Machine Learning
GET A DEEP UNDERSTANDING OF THE CONCEPTS, TECHNIQUES AND MATHEMATICAL FRAMEWORKS USED BY EXPERTS IN MACHINE LEARNING
@CourseOutline  @Video  @Concept  MachineLearning  Math  Software  Engineering  Business  Framework  Tutorial 
july 2018 by jslu
[Github] hellerve/programming-talks
There are talks on programming languages specifics as well as a more general section I call "theory". But don't expect to always get theoretical computer science for every talk there; most of them are on the architecture and design of software.
@Project  @Reference  @Video  Software  Programming  Language  OOAD  Functional  DistributedSystem  SystemArchitecture  @Concept  MachineLearning  Hardware  DevOps  Research  Math 
february 2018 by jslu
How to Read Mathematics
Mathematics has a reading protocol all its own, and just as we learn to read literature, we should learn to read mathematics.  Students need to learn how to read mathematics, in the same way they learn how to read a novel or a poem, listen to music, or view a painting.  Ed Rothstein’s book, Emblems of Mind, a fascinating book emphasizing the relationship between mathematics and music, touches implicitly on the reading protocols for mathematics.
@Article  @HOWTO  @Example  Math  InterpersonalCommunication  Symbolism  Logic  Problem-solving 
december 2017 by jslu
jwasham/coding-interview-university: A complete computer science study plan to become a software engineer.
I originally created this as a short to-do list of study topics for becoming a software engineer, but it grew to the large list you see today. After going through this study plan, I got hired as a Software Development Engineer at Amazon! You probably won't have to study as much as I did. Anyway, everything you need is here.
@Project  @CourseOutline  @Reference  Career  Software  Engineering  Programming  Language  Problem-solving  Math  Logic  Learning  Computation  Education 
december 2017 by jslu
Random: Probability, Mathematical Statistics, Stochastic Processes
Random (formerly Virtual Laboratories in Probability and Statistics) is a website devoted to probability, mathematical statistics, and stochastic processes, and is intended for teachers and students of these subjects. The site consists of an integrated set of components that includes expository text, interactive web apps, data sets, biographical sketches, and an object library. Please read the Introduction for more information about the content, structure, mathematical prerequisites,...
@Project  @Reference  @CourseOutline  Math  Education  Teaching  UnexpectednessUncertaintyAndImpermanence  Tutorial 
may 2017 by jslu
Brilliant
Effective learning is interactive, not passive. Brilliant helps you master concepts in math, science, and engineering by solving fun, challenging problems.
@Site  @Service  @CourseOutline  Math  Science  Learning  Education  ExperientialLearning  Tutorial 
may 2017 by jslu
Deep Learning in a Nutshell – what it is, how it works, why care?
the big challenges with traditional machine learning models is a process called feature extraction.. Deep learning is one of the only methods we can circumvent the challenges of feature extraction.. because deep learning models are capable of learning to focus on the right features by themselves, requiring little guidance from the programmer.. Finding out what those weights should be is the hard part of the problem, and that's done through a process called training.
@Article  @Concept  @HOWTO  @Example  Problem-solving  AI  Learning  BigData  CloudComputing  Brain  @Research  Training  Math  productivity 
march 2017 by jslu
The Map of Mathematics: Animation Shows How All the Different Fields in Math Fit Together Open Culture
Hence we now have The Map of Mathematics. Created by physicist Dominic Walliman, this new video explains “how pure mathematics and applied mathematics relate to each other and all of the sub-topics they are made from.”
@Video  @CourseOutline  @Reference  @Research  Math  WorldView  Learning  HabitRoutineAndPattern  History 
february 2017 by jslu
[1612.09375v1] Basic Category Theory
This short introduction to category theory is for readers with relatively little mathematical background. At its heart is the concept of a universal property, important throughout mathematics. After a chapter introducing the basic definitions, separate chapters present three ways of expressing universal properties: via adjoint functors, representable functors, and limits. A final chapter ties the three together.
@Article  @CourseOutline  @Concept  @Example  Math  HabitRoutineAndPattern  Tutorial 
january 2017 by jslu
[MIT] Interactive Tutorial of the Sequent Calculus
This interactive tutorial will teach you how to use the sequent calculus, a simple set of rules with which you can use to show the truth of statements in first order logic. It is geared towards anyone with some background in writing software for computers, with knowledge of basic boolean logic.
@Article  @CourseOutline  @Concept  @Example  Logic  Math  Tutorial 
january 2017 by jslu
The Probability and Statistics Cookbook
The probability and statistics cookbook is a succinct representation of various topics in probability theory and statistics. It provides a comprehensive mathematical reference reduced to its essence, rather than aiming for elaborate explanations.
@Download  @eBook  @HOWTO  @Reference  Math  Problem-solving 
november 2016 by jslu
Undergrad Math Tips
This guide was written with the calculus student in mind, though the tips are applicable to many undergraduate math classes. In the type of course this guide addresses, you will be successful if and only if you can do well on the exams. So essentially, this guide gives tips for doing well on your math exams. ... Listed below are my study suggestions broken up into things to do daily, weekly, before, during, and after an exam to ensure you do well.
@HOWTO  Math  Learning  Tip 
november 2016 by jslu
[Existential Type] The Holy Trinity
Imagine a world in which logic, programming, and mathematics are unified, in which every proof corresponds to a program, every program to a mapping, every mapping to a proof! Imagine a world in which the code is the math, in which there is no separation between the reasoning and the execution, no difference between the language of mathematics and the language of computing.
@Article  @Concept  Computation  Logic  Language  MeaningManagement  Math 
november 2016 by jslu
Eigenvectors and Eigenvalues explained visually
Eigenvalues/vectors are instrumental to understanding electrical circuits, mechanical systems, ecology and even Google's PageRank algorithm. Let's see if visualization can make these ideas more intuitive.
@Article  @Concept  @CourseOutline  @Example  Math  SensoryStimulus  MeaningManagement  Tutorial 
september 2016 by jslu
[Matthew Kirk] Why did I write a Machine Learning Book in Ruby?
This is the network effect. Basically the tool is useless unless people use it. But the network effect doesn’t apply to coding. Sure there is some benefit to being able to google the solution to a particular nltk error code you are getting. But Ruby has similar tools as well. The main difference is that you don’t get everything in one easy-install command. For instance Ruby has libsvm, ruby-fann (neural networks), tlearn (neural networks), ai4r, algorithms (k-d tree to do KNN), bayes_motel, NArray, NMatrix (new but promising), and others. If you really want more you can use JRuby to get into the massive amount of Java code that sits out there."
@Article  @Concept  @Reference  Ruby  BigData  AI  Learning  Math  Software  Programming  Language  Framework  Problem-solving 
january 2016 by jslu
[TechOrange] 從外太空懂到內子宮! 37 個免費線上課程網站打破一成不變的生活
你覺得生活一層不變嗎?是否曾經想著學習新知識,卻又因高額學費怯步,或 又以沒有時間為理由。最糟糕的情況是,繳了大筆學費又嘆無聊浪費時間。 來來來,現在就告訴你 37 個「上知天文、下知地理的實用網站,從自然科學、藝術等專業課程,到超級實用的科技網站和 apps 教學,從「鷹嘴豆泥醬實做」到「在 node.js 建構你的 apps」都傾囊相授,只要躺在沙發或划划手機就能享受互動教學,重點是免費、免費、免費。"
@Reference  @CourseOutline  Software  Programming  WebDesign  Mobile  BigData  Framework  Math  Language  SocialMedia  Music  FreeOfCharge 
december 2015 by jslu
[嫁給RD的 UI Designer] 怎麼和 RD 配合製作 UI Animation
如果設計師要產出動態特效給 RD ,他們需要幾種資訊。感謝邱政憲、Cateyes Lin 、謝孟哲的分享,綜合三位說法整理出下列 6 點"
@Article  @Reference  @HOWTO  UI  Animation  Design  InterpersonalCommunication  Interdisciplinarity  Prototyping  Math 
august 2015 by jslu
[iThome] 你能學會多少技術?
「辨識問題」是一個很重要的能力,不少人應該都有這類經驗:明明在你眼中顯而易見的問題,為何有些程式新手就是看不出問題;學的技術或理論越多,就要能辨識更多的問題,也才越能基於廣博知識來解決問題。 ... 時時承認「學不了所有的東西」,這樣我就能知道該學習的是辨識問題與面對失敗,而不是學習所有的技術,無論那是在硬體上的技術,或者是軟體!
@Article  @HOWTO  @Concept  Problem-solving  Learning  LearningFromFailure  ExperientialLearning  PersonalGrowth  Investment  Software  Hardware  Programming  Math  Language  Career 
august 2015 by jslu
[IMHO, 黑貘來說] 成為資料工程師所須要學習的 28 堂課
在這次鐵人賽的緣故, 我大概規劃了一個「成為資料工程師最初的 28 堂課」, 因為有太多人對成 Big Data / Data Mining 有興趣, 而不知道如何下手, 花了 30 天 (包含導言與結論) 列出了 28 堂課給大家參考, 雖然說是 28 堂課還不如說是 28 個科目, 只是最後發現 28 真的太少了, 所以有些科目還合併在一起. 這 28 堂課除了最後一堂外, 也是把課程分程三部份: A. 電腦相關 (Hacker), B. 數學與統計相關 (Mathematician), C. 社會人文相關 (Domain Expert)。每一類別有 9 科, 下面就是列表"
@Article  @CourseOutline  @Reference  BigData  Database  Math  Software  Engineering  UI  UX  Presentation  Research  WebDesign  KnowledgeManagement 
october 2014 by jslu
[iThome] 臺灣資料科學家直擊:Gogolook如何貫徹資料科學精神讓LINE母公司願意花6億收購
競爭者很容易學走創新的點子,但是當公司的價值奠基於創新後累積的資料或是經驗,競爭者就難以模仿。郭建甫爆料,當初Whoscall服務剛建立,使用者基礎還不夠龐大,服務中的電話黑名單還是人工蒐集網路資料來的。 ... 篩選方式是對來電進行SVM二元分類法,用定義的64個特徵當作篩選條件,來判斷電話是否為垃圾電話,越先使用的特徵權重越大,每支電話都會經過一連串是與否的判斷。不過,後來發現因為完整的經過64個特徵篩選結果雖然會比較精確,但是太過耗時,因此最後只留下20個影響較大的特徵,雖然稍微影響判斷精確度,但是這是效能與精確度權衡的結果。"
@Article  @Concept  @HOWTO  Entrepreneurship  BigData  Mobile  CrowdSourcing  Learning  Math  Feedback-receiving  Competition  ExperientialLearning  Business  ValuationAndValueAdding 
september 2014 by jslu
[iThome] 臺灣資料科學家直擊:當機器學習遇上大資料技術
過去的機器學習都是在單一機器上就可以完成,當要在分散式系統上運作,會有一些優點與缺點。林智仁說,第一項優點是,過去要從硬碟讀取TB級的資料是一件很慢且沒有效率的事,但是當有100臺電腦做這件事,資料的讀取時間就會變為百分之一,不過把資料散布在100臺電腦又是另一個議題。第二項優點是,錯誤容忍度增加,當某些資料在複製時,一臺電腦出錯,還是有其他電腦正常運作。第三項優點,使工作流不因資料的讀取而中斷。而林智仁表示,使用分散式系統的缺點理所當然使架構更加複雜,而且會有機器間溝通與同步的問題。由於機器分析的發明者,起初的設定便是在單一機器的環境下,因此沒有考慮過運算的資料讀取和中間產物的溝通。"
@Article  @Comparison  @Concept  @Research  BigData  CloudComputing  AI  Math  Computation  InterpersonalCommunication  DataSync  Fault-tolerance  Scalability  SystemArchitecture 
september 2014 by jslu
[Pragmatic Perspectives] Becoming a Data Scientist - Curriculum via Metromap ← Pragmatic Perspectives
Data Science, Machine Learning, Big Data Analytics, Cognitive Computing …. well all of us have been avalanched with articles, skills demand info graph’s and point of views on these topics (yawn!). One thing is for sure; you cannot become a data scientist overnight. Its a journey, for sure a challenging one. But how do you go about becoming one? Where to start? When do you start seeing light at the end of the tunnel? What is the learning roadmap? What tools and techniques do I need to know? How will you know when you have achieved your goal?"
@Article  @Graph  @HOWTO  BigData  Math  Programming  DataSearch  Learning  Software  Computation  Interdisciplinarity  AI  Language  PersonalGrowth 
august 2014 by jslu
[Wikipedia] Support vector machine
In machine learning, support vector machines are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. ... a support vector machine constructs a hyperplane or set of hyperplanes in a high- or infinite-dimensional space, which can be used for classification, regression, or other tasks."
@Wikipedia  AI  Learning  Math  UnexpectednessUncertaintyAndImpermanence  Software  Computation  MeaningManagement  HabitRoutineAndPattern  ExperientialLearning 
august 2014 by jslu
[Setosa] Markov Chains - A visual explanation by Victor Powell
Markov chains, named after Andrey Markov, are mathematical systems that hop from one "state" (a situation or set of values) to another. ... on top of the state space, a Markov chain tells you the probabilitiy of hopping, or "transitioning," from one state to any other state ... real modelers don't always draw out Markov chain diagrams. Instead they use a "transition matrix" to tally the transition probabilities. Every state in the state space is included once as a row and again as a column, and each cell in the matrix tells you the probability of transitioning from its row's state to its column's state. So, in the matrix, the cells do the same job that the arrows do in the diagram. ... One use of Markov chains is to include real-world phenomena in computer simulations."
@Article  @Graph  @Concept  @Example  Math  UnexpectednessUncertaintyAndImpermanence  HabitRoutineAndPattern  Computation  Google  DataSearch 
july 2014 by jslu
[陳鍾誠的網站] 免費電子書 -- 機率與統計 (使用 R 軟體)
機率與統計在科學領域、工程領域與社會研究領域都有相當強的實用性,但是要學好卻並不容易,筆者在大學時代曾經修習過機率課程,但是當我在人工智慧領域看到「貝氏網路」 (Bayisian Network)、「隱馬可夫模型」(Hidden Markov Model)、「估計最大化演算法」(Expectation-Maximization) 等機率方面的電腦應用時,才深深覺得自己並沒有學好這門學問。最近,機率與統計在「人工智慧、自然語言翻譯、語音辨識、機器人控制」等等領域,都有相當深入的進展,但是這些進展所使用到的數學,都需要相當深的機率統計基礎 ... 在實務上,我們特別重視「程式語言實作」的方式,因此我們必須採用某種程式語言來實作「機率與統計」的理論。於是我們找到了 R 這個專為機率統計而設計的語言,透過 R 語言,我們可以較為輕鬆的實作出許多用傳統語言難以實作的程式範例,這些範例將帶領著學習者深入理解機率統計的理論,並且達到「以理論指導實務、以實務印證理論」的功能。"
@eBook  @CourseOutline  Math  Software  Programming  Language  ExperientialLearning  Computation  AI  Learning  UnexpectednessUncertaintyAndImpermanence 
july 2014 by jslu
[陳鍾誠的網站] 免費電子書 -- R 統計軟體
為了學習機率統計的數學慨念,我們使用 R 軟體進行實作,以便將理論化為實務。如果您也想學習機率統計,並且希望能透過程式與操作體會這些數學的意義,那麼本書將會是您所需要的。本書與 「機率與統計--使用 R 軟體」 乃是姊妹作,同時閱讀將有助於您兼顧理論與實作。"
@eBook  @CourseOutline  Math  Software  Programming  Language  Tutorial 
july 2014 by jslu
[知乎專欄] 如果看了這篇文章你還不懂傅里葉變換,那就過來掐死我吧 - 與時間無關的故事
如果我說我能用前面說的正弦曲線波疊加出一個帶90度角的矩形波來,你會相信嗎?你不會,就像當年的我一樣。但是看看下圖 ... 隨著疊加的遞增,所有正弦波中上升的部分逐漸讓原本緩慢增加的曲線不斷變陡,而所有正弦波中下降的部分又抵消了上升到最高處時繼續上升的部分使其變為水平線。一個矩形就這麼疊加而成了。但是要多少個正弦波疊加起來才能形成一個標準90度角的矩形波呢?不幸的告訴大家,答案是無窮多個。不僅僅是矩形,你能想到的任何波形都是可以如此方法用正弦波疊加起來的。這是沒有接觸過傅里葉分析的人在直覺上的第一個難點,但是一旦接受了這樣的設定,遊戲就開始有意思起來了。"
@Article  @Concept  @Example  Math  Engineering  Tutorial 
june 2014 by jslu
[CodeData] MySQL 超新手入門(4)運算式與函式 by Michael
運算式(expressions)已經在查詢敘述中使用過,例如算數運算與「WHERE」子句中的條件判斷。雖然目前只有討論查詢資料的部份,不過你在任何地方都有可能使用運算式來完成你的工作。一個運算式中可以包含值(literal values)、運算子和函式,都會在這裡討論它們的細節與應用。" ... & 介紹 GROUP BY 子句的用法
@Article  @HOWTO  @Example  Database  Language  Software  Math  Tutorial 
january 2014 by jslu
[Inside] 對九個超級程式設計師的採訪
他是否有能力能和別人進行簡單的溝通,告訴別人他要幹什麼,怎麼幹。這個能力可以告訴別人為什麼你幹的事是非常重要的,並不是所有的人都有這個能力。也就是說,有一些人可以寫出很不錯的程式,但他們並不一定能解釋這些程式,他們也並不一定有好的品味,但是程式可以運行得不錯。有時,你需要另一個人(有那種不錯的品味的人)把他的程式轉成更好的形式。也就是說,任何一個程式設計師都需要那種可以用清晰的程式來解決複雜問題的基礎能力。"
@Article  Celebrity  Software  Programming  Engineering  Teamwork  InterpersonalCommunication  Writing  Problem-solving  Math  Education  Learning  WebApp  Ruby  Editor  SourceCodeManagement 
january 2014 by jslu
Data Structure Visualization
The best way to understand complex data structures is to see them in action. We've developed interactive animations for a variety of data structures and algorithms. Our visualization tool is written in javascript using the HTML5 canvas element, and run in just about any modern browser -- including iOS devices like the iPhone and iPad, and even the web browser in the Kindle!"
@Project  @Example  @HOWTO  Math  Computation  Programming  Software  Animation  JavaScript  WebDesign  Presentation 
december 2013 by jslu
[Sijin Joseph] Programmer Competency Matrix
Note that the knowledge for each level is cumulative; being at level n implies that you also know everything from the levels lower than n."
Software  Programming  KnowledgeManagement  Database  Agility  Math  Framework  SystemArchitecture  PersonalGrowth  Integration  API  Engineering  InterpersonalCommunication  Career  HabitRoutineAndPattern  Language  Problem-solving  @Comparison  Productivity 
october 2013 by jslu
iOS 7 中的動態焦點設計及 Parallax 空間動態中的速率曲線分析 | T客邦 - 我只推薦好東西
作為介面體驗的重要組成部分,產品介面的動態設計也不僅僅是用來增加視覺方面的感官刺激,而更多的是影響使用者對產品的感知和理解。iOS 平台的動態設計,從第一代 iPhone 發佈起即透過產品的動態表現,體現了介面在 X、Y、Z 軸之間的空間層級關係。透過 iOS 平台的動態表現,使用者可以輕鬆地理解螢幕中所存在的「世界」,以及「我」在這其中所處的位置座標。 ... 除了時間和加速度曲線的變化外,iOS 7 的動態速率還包含了一個全新維度,就是與其全新「Parallax」解構相呼應的空間速率。"
Software  Animation  SensoryStimulus  UI  Math  @Example  Feedback-receiving  Self-awareness  Design  AttentionManagement  3D  UX  @Article 
october 2013 by jslu
[Ant] Best practicing for password protection
在安全性及效能的綜合考量下,筆者建議 “隨機加料式雜湊法”, “使用兩種以上的隨機加料式雜湊演算法” 或 “HMAC 隨機加料式演算法"。愈後者安全性愈高,但效能的要求也愈高。"
Tutorial  Software  Programming  Math  @Example  Security  Computation  @Concept  WebDesign  @Research  @Comparison  @Article  @HOWTO 
october 2013 by jslu
[iThome] 佇列是平衡服務品質及成本的關鍵
想要好品質往往需付出更多成本,想省成本,通常就得犧牲一些服務品質。因此,必須找到平衡點,而佇列就是一種控制的方式,透過限制條件的確認,可以建立排隊的模型,了解你能得到的品質 ... 對工作佇列來說,即使工作抵達系統的速度「有時候」會高過伺服器消費工作的速度,但是因為畢竟系統不是持續處於尖峰的負載,所以透過佇列中排隊的機制將工作「暫存起來」,使得伺服器還是可以接著把工作完成。"
Software  UnexpectednessUncertaintyAndImpermanence  Math  CloudComputing  Fault-tolerance  @Example  SystemArchitecture  Integration  Engineering  InterpersonalCommunication  @Concept  @Comparison  Balance  DataSync  @Article  MultiLayeredStructure  ConflictResolution  Paradox  AssetAllocation  @HOWTO  Tip  Concurrency 
september 2013 by jslu
[有物報告] 動畫角色栩栩如生:結合肢體與科技的創作
在特殊服裝表面加上由高反光材質製作的反光球,並在特定位置安裝,由攝影機接收自身打出的反射光線(由反光球反射), 這種系統稱為被動式的動態捕捉系統。 ... 在被動式系統中,攝影機會打出一道道光線(通常是紅色)。光線碰到反光球後,反射回攝影機。攝影機接收到反射的光線後會回傳資料給系統,系統便根據逆平方法則(Inverse-square law)來計算該反光點在空間中的位置。"
@Article  @Example  @Concept  @HOWTO  3D  Filmmaking  Hardware  Math  Tutorial 
january 2013 by jslu
[iCoding] 「資料探勘」幼幼班
「資料探勘」是一個「嘗試從一大組資料當中找出一些特徵樣式(pattern)的過程」。 ... 資料探勘強調的是「探勘」或是「探索未知(detecting something new)」這件事。很多人誤以為資料探勘包括任何形式的大規模(尤其是強調巨量,例如大資料 - big data)的資料或資訊的處理過程,例如一些資料收集、擷取、放置、分析與統計分析,甚至人工智慧、機器學習、Business Intelligence、電腦輔助決策系統等,都不是資料探勘。 ... 另外,資料探勘和「應用」資料探勘技術其實是兩件事情,一個是對未知模型的探索,另一個是拿已知的模型進行應用,一個是模型創造者,一個是模型使用者,如果沒有切割十分清楚很容易被誤解。"
@Article  @Concept  @Comparison  HabitRoutineAndPattern  Math  BigData  AI 
september 2012 by jslu
[SixRevisions] The 960 Grid System Made Easy
This article is for web designers and front-end web developers who are interested in grid-based layout systems but are at a loss on how to decipher them. We’ll focus specifically on the 960 Grid System, but after reading this guide, you’ll find that most of the other grid systems out there are similar and will make much more sense after you understand a few basic principles. ... The 960 Grid System is simply a way to lay out websites using a grid that is 960 pixels wide. The reason it’s 960 pixels wide is because the number 960 makes for a lot of clean divisions utilizing whole numbers when factoring in column widths and margins. And it fits nicely on the majority of screens. ... When you look at the diagrams above, consider each of the dark blue horizontal bars as a CSS class in the 960 Grid System. To create an object in your layout that is the width of one of those bars, you simply assign the proper class to your div–that’s it!"
@Article  @Concept  @Example  @Reference  WebDesign  CSS  Framework  Productivity  Math  Creativity  Tutorial 
may 2011 by jslu
[Archifield 建築論壇] 為什麼設計教育必須改變? - 唐.諾曼
早期的工業設計成品大多是實體產品。然而時至今日,設計師的工作還擴及組織架構、社會問題、互動、服務與經驗設計。許多問題牽涉到複雜的社會與政治議題,結果設計師變成應用行為科學家,但他們在這方面的教育卻嚴重不足。 ... 舊時代的技能(如素描與繪圖、模型與模具)必須被新時代的技能(如程式撰寫、互動與人類認知)補強,甚至被取代。快速製作原型與使用者測試是必要知識,意味著設計師必須懂得一些社會與行為科學、統計學、和實驗設計。 ... 設計師經常用貧乏的統計和行為差異知識在檢視自己的設計。他們不知道下意識的偏見會導致他們只看見自己想看的,而非實際發生的現象。 ... 設計師沈淪於兩種病態心理:不知道自己的無知,和更糟的,無知卻自以為是。當面對人類行為--亦即認知科學--時,後者尤其明顯。 ... 服務設計、互動設計和經驗設計等新興設計領域非關實體物件,對繪圖、材料知識或製造的技能要求不高,反而對社會科學、故事建構、後台運作與互動流程等知識有迫切需要。"
@Article  @Research  Design  Interdisciplinarity  Education  CognitiveScience  CognitiveBias  Science  Math  UX  Self-awareness  Feedback-receiving  Happiness  Art  Industry  Integration  LatentDesire  HumanNature  Programming  InterpersonalCommunication  Prototyping  Adaptability  ProgressiveImprovement  FutureTrend 
december 2010 by jslu
[Wikipedia] Gini coefficient
a measure of statistical dispersion developed by the Italian statistician Corrado Gini... It is commonly used as a measure of inequality of income or wealth... When used as a measure of income inequality, the most unequal society will be one in which a single person receives 100% of the total income and the remaining people receive none (G=1); and the most equal society will be one in which every person receives the same percentage of the total income (G=0)."
@Wikipedia  Economics  Finance  Politics  Sociology  Math  IndicatorIndexAndRatio  MShapedSociety 
february 2010 by jslu
[Wikipedia] Control engineering
the engineering discipline that applies control theory to design systems with predictable behaviors... It allows one to understand a physical system in terms of its inputs, outputs and various components with different behaviors using mathematical modeling, control it in a desired manner with the controllers designed using control systems design tools, and implement the controller on the physical system employing available technology... Control engineering has diversified applications that include science, finance management, and even human behavior."
@Wikipedia  @Research  Engineering  Feedback-receiving  SystemsTheory  Math  Interdisciplinarity 
july 2009 by jslu
[The Biggest Ideas] You Have Three Brains
One thing is clear though: you have three brains. There are three brains nested within your skull: the lizard brain, the dog brain, and the human brain... Consider this: language lies in the human brain, but emotions lie within the separate dog and lizard brains. So the emotions are in a different world from language entirely. Not only that, reason too lives in the new human brain while emotions live in the older brains... The older brains cannot speak. They can only feel and act. This is where the self-contradictory nature of so much human behavior comes from... The way the neo-cortical memory degrades while the limbic memory lasts may also have something to do with the differing ages at which certain human capacities peak... Can we better integrate our three brains? It turns out that meditation integrates the brains. It rewires and harmonizes them."
@Article  @Research  @Example  Brain  Science  Paradox  Language  Irrationality  Emotion  LatentDesire  Integrity  HumanNature  Politics  Leadership  ExperientialLearning  Wisdom  Math  Writing  Music  Philosophy  Meditation  Neuroscience 
may 2009 by jslu
[Wikipedia] World view
the framework of ideas and beliefs through which an individual interprets the world and interacts with it... a consistent (to a varying degree) and integral sense of existence and provides a framework for generating, sustaining, and applying knowledge... The language of a people reflects the Weltanschauung of that people in the form of its syntactic structures and untranslatable connotations and its denotations... the fundamental cognitive, affective, and evaluative presuppositions a group of people make about the nature of things, and which they use to order their lives... a framework for generating various dimensions of human perception and experience like knowledge, politics, economics, religion, culture, science, and ethics... A worldview can be considered as comprising a number of basic beliefs which are philosophically equivalent to the axioms of the worldview considered as a logical theory."
@Wikipedia  @Research  WorldView  Belief  PerspectiveAndFraming  Philosophy  CognitiveScience  Language  Consciousness  Culture  Politics  Economics  Subjectivity  Science  Literature  Math  Logic  Globalization  Gödel 
may 2009 by jslu
[Computational Complexity] Foundations of Complexity
In the first year of this blog I wrote a series of 'lessons' to give an informal introduction to computational complexity but I never wrote a single post that links to them all."
@Reference  @Column  Computation  Math  Tutorial 
may 2009 by jslu
[Wikipedia] Elasticity (economics)
the ratio of the percent change in one variable to the percent change in another variable... a tool for measuring the responsiveness of a function to changes in parameters in a relative way... a popular tool among empiricists because it is independent of units and thus simplifies data analysis."
@Wikipedia  Finance  Economics  SupplyAndDemand  Math  Adaptability  Marginality  ProactiveChange 
april 2009 by jslu
Presentation Preparation - TeX4PPT
TeX4PPT is designed following the philosophy of TeXPoint, to enable PowerPoint to typeset sentences and equations using the power of TeX."
Math  Software  Windows  Plug-in  @Project  Presentation  LaTeX  PowerPoint  MSOffice 
january 2009 by jslu
[Wikipedia] Infinity
Infinity (symbolically represented with ∞) comes from the Latin infinitas or 'unboundedness.' It refers to several distinct concepts (usually linked to the idea of 'without end') which arise in philosophy, mathematics, and theology."
@Wikipedia  Math  Philosophy  Theology  Logic  Paradox  Intuition  Unlimitedness 
august 2008 by jslu
[Wikipedia] The Emperor's New Mind
a 1989 book by mathematical physicist Sir Roger Penrose. Penrose presents the argument that human consciousness is non-algorithmic, and thus is not capable of being modeled by a conventional Turing machine-type of digital computer. Penrose hypothesizes that quantum mechanics plays an essential role in the understanding of human consciousness. The collapse of the quantum wavefunction is seen as playing an important role in brain function."
@Wikipedia  Book  AI  Consciousness  Computation  QuantumPhysics  Science  Philosophy  Math  CognitiveScience  Interdisciplinarity 
august 2008 by jslu
[Wikipedia] Empirical limits in science
In philosophy of science the empirical limits of science define problems with observation, and thus are limits of human ability to inquire and answer questions about phenomena. These include topics such as infinity, the future and god."
@Wikipedia  Science  Philosophy  Subjectivity  Math  QuantumPhysics  Logic  Unlimitedness 
august 2008 by jslu
[Wikipedia] Chaos theory
chaos theory describes the behavior of certain dynamical systems – that is, systems whose state evolves with time – that may exhibit dynamics that are highly sensitive to initial conditions (popularly referred to as the butterfly effect)"
@Wikipedia  @Research  Math  Science  SystemsTheory  Electronics  Computation 
june 2008 by jslu
[Wikipedia] Cognitive science of mathematics
the study of mathematical ideas (concepts) using the techniques of cognitive science. It proposes to ground the foundations of mathematics in the empirical study of human cognition and metaphor, and to analyze mathematical ideas in terms of the human experiences, metaphors, generalizations, and other cognitive mechanisms giving rise to them... If human intuition appears to be inconsistent with formal mathematics, this gives rise to the question of where formal mathematics comes from."
@Wikipedia  @Research  Math  CognitiveScience  Philosophy  Finance  Metaphor  CognitiveBias  Economics  Intuition  Education 
may 2008 by jslu
[Wikipedia] Self-reference
Self-reference is possible when there are two logical levels, a level and a meta-level. It is most commonly used in mathematics, philosophy, computer programming, and linguistics. Self-referential statements can lead to paradoxes."
@Wikipedia  @Example  Paradox  Language  Literature  Philosophy  Math  Logic  Computation  Subjectivity  Feedback-receiving  Self 
april 2008 by jslu
[Wikipedia] Mathematics
quantity(arithmetic), structure(algebra), space(geometry), change(analysis)
@Wikipedia  @Reference  Math  Research  Science 
march 2008 by jslu
[Computational Complexity] Math books you can actually read
原來花幾十年的時間去讀完一本數學書的大有人在... :D
@Article  Math  Research  Book  Learning 
january 2008 by jslu
[Computational Complexity] Today is Knuth's 70th birthday!!
I want to solve problem X and I'll use whatever math I need to solve it, even if I have to develop it myself."
@Article  Celebrity  Research  Math  Learning 
january 2008 by jslu
[Wikipedia] 悖論 (paradox)
“古今中外有不少著名的悖論,它們震撼了邏輯和數學的基礎,激發了人們求知和精密的思考...。解決悖論難題需要創造性的思考,悖論的解決又往往可以給人帶來全新的觀念。”
@Wikipedia  Paradox  Math  Logic  Philosophy 
june 2007 by jslu
[石頭閒語] 維根斯坦眼中的數學並非不可言的
維根斯坦在《邏輯哲學論》中說「'語言的邊界就是世界的邊界'」。數學所能表達的意涵有其邊界,在邊界以外之事,「'不要想,但要看'(《哲學研究》)」。" - comments 的部份也不錯。
@Article  Philosophy  Math  Language  Economics  Unlimitedness  WorldView 
june 2007 by jslu
[聽雨塵心@含藏識] 【數學故事】哥德爾不完備性定理淺釋
彭羅斯對強AI質疑的論點主要基於兩個方面,第一個方面來自數學和邏輯學,他使用著名的哥德爾不完備定理(Godel Incomplete Theorem)和圖林的停止問題(Turing's Halting Problem)證明了帕拉圖理念世界(Platonic World)裡存在著大量不可計算的問題,即不能使用計算機算法獲得由人類直覺天才取得的大多數數學成果,而這,尚不包括人類對藝術等領域的認知和理解。... 彭羅斯一步一步地把嚴密的數學推理用到證明計算機不能代替人腦作數學思維。彭羅斯這一推理雖然只用在數學直覺上,卻也可以同樣用在人的其他意識經驗上面,例如,領會特徵(sensory qualia)、痛苦和快樂的感受、意志的感情(feelings of volition)、意向性(intentionality)等上,只是因為這些意識特徵不像數學直覺一樣,有與邏輯較明顯劃分的界線和符號推理工具,能夠被彭羅斯拿來作為有力的武器罷了。"
@Article  @Research  Gödel  Philosophy  Math  Paradox  AI  Logic  Anecdote  Intuition  Computation  Consciousness  Neuroscience  QuantumPhysics  Interdisciplinarity  SensoryStimulus 
june 2007 by jslu
[CCIM-網絡基督使團] 哥德爾不完備性定理(theorem of incompleteness):人間邏輯與神聖三一邏輯
什麼是真呢?在哥德爾之前,都相信凡是真的都能被證明,這以大數學家希爾伯特(David Hilbert, 1862-1943)為代表的形式主義(Formalism),主張一切數學都必須被證明建立在公理化的基礎上。主張邏輯原子主義(Logic Atomism)的羅素(Bertrand Russell, 1872-1970),則相信一切語言都可建立在最基本的意義原子層次上,並以邏輯符號表達... 哥德爾的傑出貢獻在於提出:凡是命題為真的,不見得一定可以被證明。"
@Article  Gödel  Christianity  Spirituality  Math  Logic  Paradox  Philosophy  Theology  Self  Language 
june 2007 by jslu
[心靈小憩] 試談理性認識的侷限 (之三)
哥德爾不完備定理在不同的領域引人注目,其地位就類似於物理學中量子力學的測不準原理,電腦程式語言的丘奇-圖林之不可判定定理,形式語言中塔斯基的真概念不可定義性原理,以及語言哲學中蒯因的翻譯不確定性論題,它們都在不同的方面界定了認知或理性能力的範圍。"
@Article  Gödel  AI  Spirituality  Math  Philosophy  Paradox  Logic  Intuition  QuantumPhysics  CognitiveScience  SystemsTheory  Interdisciplinarity  Unlimitedness  Irrationality 
june 2007 by jslu
[Wikipedia] Gödel's incompleteness theorems
two theorems of mathematical logic that state inherent limitations of all but the most trivial axiomatic systems for arithmetic. They state that any effectively generated formal theory in which all arithmetic truths can be proved is inconsistent; hence, any such consistent formal theory that can prove some arithmetic truths cannot prove all arithmetic truths." - 二十世紀最重要的數學定理,影響力橫跨科學與人文,直指人類心靈的內在運作。
@Wikipedia  @Research  Gödel  Math  Philosophy  Logic  Paradox  Spirituality  Computation  AI  Celebrity  Unlimitedness 
may 2007 by jslu
Shtetl-Optimized
The Blog of Scott Aaronson
@Blog  @Research  Math  Celebrity 
april 2007 by jslu
[Wikipedia] Reductionism
化約主義 "A)an approach to understanding the nature of complex things by reducing them to the interactions of their parts, or to simpler or more fundamental things B)a philosophical position that a complex system is nothing but the sum of its parts... A contrast to the reductionist approach is holism or emergentism. Holism recognizes the idea that things can have properties as a whole that are not explainable from the sum of their parts (emergent properties).
@Wikipedia  Philosophy  HolismAndOneness  Math  Science  SystemsTheory  Cybernetics  Subjectivity 
april 2007 by jslu
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