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FT-series

Symbolic Representations of Time Series... SAX is just as good as other representations, or working

Symbolic Representations of Time Series... SAX is just as good as other representations, or working on the raw data for most problems (Slides shown at the end of this presentation)

標(biāo)簽： Representations representations Symbolic working

上傳時(shí)間： 2014-01-16

上傳用戶：dongqiangqiang
This code is written in C and it is used to calculate the adjective series of numbers.

This code is written in C and it is used to calculate the adjective series of numbers.

標(biāo)簽： adjective calculate written numbers

上傳時(shí)間： 2017-04-18

上傳用戶：onewq
I CAME BACK I BRING LOTS OF THING TO U ALL THIS TUTORIAL FOR DAY3 SESSION SERIES OF UNIX HARDWARE AN

I CAME BACK I BRING LOTS OF THING TO U ALL THIS TUTORIAL FOR DAY3 SESSION SERIES OF UNIX HARDWARE AND NETWORKING CONCEPTS

標(biāo)簽： HARDWARE TUTORIAL SESSION SERIES

上傳時(shí)間： 2017-04-26

上傳用戶：liglechongchong
A fourier filter for time-series signals. Does not require the Signal Processing Toolbox. There is

A fourier filter for time-series signals. Does not require the Signal Processing Toolbox. There is an interactive version with sliders that allow you to adjust the filter parameters continuously while observing the effect on your signal dynamically.

標(biāo)簽： time-series Processing fourier Toolbox

上傳時(shí)間： 2013-12-19

上傳用戶：change0329
Interactive smoothing for time-series signals, with sliders that allow you to adjust the smoothing

Interactive smoothing for time-series signals, with sliders that allow you to adjust the smoothing parameters continuously while observing the effect on your signal dynamically. Run SmoothSliderTest to see how it works.

標(biāo)簽： smoothing Interactive time-series signals

上傳時(shí)間： 2014-12-07

上傳用戶：xinyuzhiqiwuwu
利用PWM功能實(shí)現(xiàn)語音播放功能。本系統(tǒng)應(yīng)用于Suplus SPMC65* Series上

利用PWM功能實(shí)現(xiàn)語音播放功能。本系統(tǒng)應(yīng)用于Suplus SPMC65* Series上，使用PWM功能播放WAV格式的語音文件。

標(biāo)簽： Suplus Series SPMC PWM

上傳時(shí)間： 2017-05-04

上傳用戶：linlin
【書名】非線性時(shí)間序列分析【原書名】 Nonlinear Time Series Analysis 【原出版社】 Cambridge University Press 【作者】Holge

【書名】非線性時(shí)間序列分析【原書名】 Nonlinear Time Series Analysis 【原出版社】 Cambridge University Press 【作者】Holger Kantz,Thomas Schreiber [同作者作品] 【叢書名】劍橋非線性科學(xué)系列【出版社】清華大學(xué)出版社【書號(hào)】 7302039062 【出版日期】 2001 年3月【開本】 16開【頁碼】 304 【版次】1-3

標(biāo)簽： University Nonlinear Cambridge Analysis

上傳時(shí)間： 2013-12-27

上傳用戶：as275944189
Tools for development on the Archos Gmini 100 & 200 series -- GNU Binutils for CalmRisc16 -- gcc for

Tools for development on the Archos Gmini 100 & 200 series -- GNU Binutils for CalmRisc16 -- gcc for CalmRisc16 -- Gmini 1xx & 2xx emulator

標(biāo)簽： for development Binutils CalmRisc

上傳時(shí)間： 2013-12-24

上傳用戶：waitingfy
混沌時(shí)間序列預(yù)測(cè)(chaotic time series prediction) RBF神經(jīng)網(wǎng)絡(luò)一步預(yù)測(cè) - Prediction_RBFMain_RBF.m RBF神經(jīng)網(wǎng)絡(luò)多步預(yù)測(cè) - Pred

混沌時(shí)間序列預(yù)測(cè)(chaotic time series prediction) RBF神經(jīng)網(wǎng)絡(luò)一步預(yù)測(cè) - \Prediction_RBF\Main_RBF.m RBF神經(jīng)網(wǎng)絡(luò)多步預(yù)測(cè) - \Prediction_RBF\Main_RBF_MultiStepPred.m Volterra級(jí)數(shù)一步預(yù)測(cè) - \Prediction_Volterra\Main_Volterra.m Volterra級(jí)數(shù)多步預(yù)測(cè) - \Prediction_Volterra\Main_Volterra_MultiStepPred.m

標(biāo)簽： Prediction_RBFMain_RBF prediction RBF chaotic

上傳時(shí)間： 2014-08-21

上傳用戶：yangbo69
GCC arm startup example2 for LPC series

GCC arm startup example2 for LPC series

標(biāo)簽： example2 startup series GCC

上傳時(shí)間： 2014-01-03

上傳用戶：heart520beat