1. The problem statement, all variables and given/known data A noisy but slowly-shifting sensor signal is being filtered with a low-pass, finite impulse response filter. What is the mean delay and expected SNR boost (noise standard deviation of output compared to input) for two filter variations: N filter taps uniformly weighted: y[n] = (x[n] + ... + x[n - N + 1])/N M filter taps harmonically weighted: z[n] = (M*x[n] + (M-1)*x[n-1] ... 1*x[n - M + 1])/(M*(M+1)/2) What depths (N and M) for each setup are needed to boost the SNR by a factor of 5? Which setup a) or b) has the lowest mean delay at the required depth? Which setup would you recommend gives the best tradeoff between SNR and delay? 2. Relevant equations 3. The attempt at a solution I believe that the width of each FIR filter would correspond to a specific gain for the output signal, would I be correct in assuming that the summation of the co-efficients would give me said answer? I am interviewing with Motorola for an internship, and have not completed my DSP coursework, since I am enrolled in it right now. Can anyone shed some light into what I need to do?