# deciphering the frequency response from the input data

Newbie to Signal processing, sorry if the question is basic. I have a data set consisting of 601 values. The values being time Vs voltage . The voltage values have transients in them. My aim is to filter out these transients using an FIR filter. But i'm still far from doing that. This is my voltage Vs Time plot.

I plotted the fft of voltage and this is what i got.

I read up that fft basically divides my sampling frequency,Fs, into N equal parts (N= 601, Total number of values). According to my (voltage Vs Time) plot, my Fs=2500Hz (by calculating Ts as the difference between consecutive values of time from data set).Then,2500/601 gives 4.159 as the first point in my fft. Is this even correct?

Going by the above,the strength of the signal is greatest at the 11th value (ie,10*4.159 =41.59 Hz) and the 592nd value (591*4.159=2458 Hz).Now, What significance does this information hold if i need to design a filter to eliminate the transients? What do information do i take away exactly, by performing the fft of the voltage signal?

Thanks

Since the signal is most certainly real-valued, you can ignore the FFT values after $f_s/2$ (or sample 300 in your plot) since they will mirror the first ones. With a sampling frequency of 2500Hz, the highest frequency in your signal can be 1250Hz. If you have higher frequencies and don't filter them prior to sampling, you will get aliasing. Look up the sampling theorem for more information, it's quite important when working with sampled signals.