データの解析

遅延、フィードバック、励起レベルなどのデータ特性の決定

関数

`bode`	周波数応答、またはゲインと位相データのボード線図
`bodemag`	周波数応答のゲインのみのボード線図
`plot`	Plot input and output channels of `iddata` object
`advice`	Analysis and recommendations for data or estimated linear models
`delayest`	Estimate time delay (dead time) from data
`isreal`	モデルパラメーターまたはデータ値が実数かどうかを判別
`realdata`	Determine whether `iddata` is based on real-valued signals
`feedback`	Identify possible feedback data
`pexcit`	Level of excitation of input signals
`impulseest`	Nonparametric impulse response estimation
`etfe`	Estimate empirical transfer functions and periodograms
`spa`	Estimate frequency response with fixed frequency resolution using spectral analysis
`spafdr`	Estimate frequency response and spectrum using spectral analysis with frequency-dependent resolution

iddataPlotOptions Option set for plot when plotting data contained in an iddata object

例および操作のヒント

How to Plot Data in the App

After importing data into the System Identification app, as described in データの表現, you can plot the data.

How to Plot Data at the Command Line

The following table summarizes the commands available for plotting time-domain, frequency-domain, and frequency-response data.

How to Analyze Data Using the advice Command

You can use the advice command to analyze time- or frequency- domain data before estimating a model. The resulting report informs you about the possible need to preprocess the data and identifies potential restrictions on the model accuracy. You should use these recommendations in combination with plotting the data and validating the models estimated from this data.

Identify Delay Using Transient-Response Plots

You can use transient-response plots to estimate the input delay, or dead time, of linear systems. Input delay represents the time it takes for the output to respond to the input.

概念

Is Your Data Ready for Modeling?

Before you start estimating models from data, you should check your data for the presence of any undesirable characteristics. For example, you might plot the data to identify drifts and outliers. You plot analysis might lead you to preprocess your data before model estimation.

System Identification Toolbox ドキュメンテーション

サポート

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