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Does the zero-value or sensitivity of an accelerometer changes over time? I.e is there something similar to the bias drift effect for gyroscopes, for accelerometers?
Yes. They also depend on temperature. And the temperature coefficient of offset (TCO) and the temperature coefficient of sensitivity (TCS) are different for the three axes. That's why you have the x,y,z calibration commands.
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I asked a question earlier that might have been too specific so I'll ask again in more general terms. How does error get propagated backwards through a pooling layer when there are no weights to train? In the tensorflow video at 6:36 https://www.youtube.com/watch?v=Y_hzMnRXjhI there's a GlobalAveragePooling1D after Embedding, How does the error go backwards?
A layer doesn't need to have weights in order to back-prop.
You can compute the gradients of a global avg pool w.r.t the inputs - it's simply dividing by the number of elements pooled.
It is a bit more tricky when it comes to max pooling: in that case, you propagate gradients through the pooled indices. That is, during back-prop, the gradients are "routed" to the input elements that contributed the maximal elements, no gradient is propagated to the other elements.
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The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm.
So how to avoid local minima in Back propagation algorithm.
In local minimum a gradient of an error function is a zero vector - so backprop - which is using a gradient - cannot move your parameters any further and finishes training.
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I have plotted the standard deviation of different regions.Can anyone help me to get the conclusions from this boxplot. I just want to conclude the properties of regions. In this figure, eigth object is odd one. What is the significance of whiskers?
How to change the xlabel as region1 ,region2 etc
Coclusions: wide part of your data does not follow a normal distribution. You need something like Violin Plots to see what is rally happening in your data.
Specially for 3-7, as it seems that the number of the outliers is too big.
But remember: Conclusions are obtained from data, not from the plotting option you chose for your data!
about changing the xlabel.... have you tried the function xlabel....?
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While solving a puzzle, I ended up having a complexity of T(n)=T(n-3)+T(n-5).
I was trying subtraction method. But I am unable to solve this. Please explain what should be the procedure.
This is a linear homogeneous difference equation with constant coeffs.. It is usually solved by transforming it to the complex plane and solving a polynomial.
Without a CS background (as you state), I'm afraid the details wouldn't fit in here. Start with the Wikipedia entry, if you're interested.
If you want to skip to the final solution, here is the Wolfram Alpha for it.
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How can I detect P-R interval from an ECG signal using MATLAB ? Can anyone give me code or any steps to determine this ?
Find the P wave (s).
Find the QRS complex(es).
Pair up a QRS complex and its preceding P wave. Make sure to avoid cases where there is a PVC or other abnormal beat in between.
Subtract the time of the P wave from the time of the R peak in the QRS complex.