Low Pass and High Pass filters detailed explanation here is usefull link.
http://en.wikipedia.org/wiki/ High-pass_filter
http://en.wikipedia.org/wiki/ Low-pass_filter
You can also check out adaptive filtering in this example from Apple: http://developer.apple.com/ library/ios/#samplecode/ AccelerometerGraph/Listings/ AccelerometerFilter_m.html#// apple_ref/doc/uid/DTS40007410- AccelerometerFilter_m- DontLinkElementID_4
Just note that a high pass filter allows high frequencies to pass through and attenuates lower frequencies. The opposite is true for a low pass filter. Think of high frequency events as events that happen suddenly or fast so a sudden bump on the road will cause input with a higher frequency. A low frequency is going to be average data that you're getting from background noise, slower motion etc.
So if you want to detect smoothed out changes you should use a low-pass filter to filter out any sudden jerky motion. If you want to detect quick instantaneous changes in input you'll need to use a high-pass filter instead. You need to think about what type of motion is happening in your use case and apply the correct filter.
http://en.wikipedia.org/wiki/
http://en.wikipedia.org/wiki/
You can also check out adaptive filtering in this example from Apple: http://developer.apple.com/
Just note that a high pass filter allows high frequencies to pass through and attenuates lower frequencies. The opposite is true for a low pass filter. Think of high frequency events as events that happen suddenly or fast so a sudden bump on the road will cause input with a higher frequency. A low frequency is going to be average data that you're getting from background noise, slower motion etc.
So if you want to detect smoothed out changes you should use a low-pass filter to filter out any sudden jerky motion. If you want to detect quick instantaneous changes in input you'll need to use a high-pass filter instead. You need to think about what type of motion is happening in your use case and apply the correct filter.
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