From 8764fcddb79a63fb6cb8ad8f61b1c84356a107fe Mon Sep 17 00:00:00 2001 From: Erik Strand <erik.strand@cba.mit.edu> Date: Wed, 8 May 2019 11:40:32 -0400 Subject: [PATCH] Add questions for pset 12 --- _psets/12.md | 159 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 159 insertions(+) create mode 100644 _psets/12.md diff --git a/_psets/12.md b/_psets/12.md new file mode 100644 index 0000000..6eb4be2 --- /dev/null +++ b/_psets/12.md @@ -0,0 +1,159 @@ +--- +title: Problem Set 12 +--- + +## (15.1) + +### (a) + +{:.question} +Show that the circuits in Figures 15.1 and 15.2 differentiate, integrate, sum, and difference. + +### (b) + +{:.question} +Design a non-inverting op-amp amplifier. Why are they used less commonly than inverting ones? + +### (c) + +{:.question} +Design a transimpedance (voltage out proportional to current in) and a transconductance (current out +proportional to voltage in) op-amp circuit. + +### (d) + +{:.question} +Derive equation (15.16). + +## (15.2) + +{:.question} +If an op-amp with a gain–bandwidth product of 10 MHz and an open-loop DC gain of 100 dB is +configured as an inverting amplifier, plot the magnitude and phase of the gain as a function of +frequency as $$R_\text{out}/R_\text{in}$$ is varied. + +## (15.3) + +{:.question} +A lock-in has an oscillator frequency of 100 kHz, a bandpass filter Q of 50 (re- member that the Q +or quality factor is the ratio of the center frequency to the width between the frequencies at which +the power is reduced by a factor of 2), an input detector that has a flat response up to 1 MHz, and +an output filter time constant of 1 s. For simplicity, assume that both filters are flat in their +passbands and have sharp cutoffs. Estimate the amount of noise reduction at each stage for a signal +corrupted by additive uncorrelated white noise. + +## (15.4) + +### (a) + +{:.question} +For an order 4 maximal LFSR work out the bit sequence. + +### (b) + +{:.question} +If an LFSR has a chip rate of 1GHz, how long must it be for the time between repeats to be the age +of the universe? + +### (c) + +{:.question} +Assuming a flat noise power spectrum, what is the coding gain if the entire sequence is used to send +one bit? + +## (15.5) + +{:.question} +What is the SNR due to quantization noise in an 8-bit A/D? 16-bit? How much must the former be +averaged to match the latter? + +## (15.6) + +{:.question} +The message 00 10 01 11 00 ($$c_1$$, $$c_2$$) was received from a noisy channel. If it was sent by +the convolutional encoder in Figure 15.20, what data were transmitted? + +## (15.7) + +{:.question} +This problem is harder than the others. + +### (a) + +{:.question} +Generate and plot a periodically sampled time series {$$t_j$$} of N points for the sum of two sine +waves at 697 and 1209 Hz, which is the DTMF tone for the number 1 key. + +### (b) + +{:.question} +Calculate and plot the Discrete Cosine Transform (DCT) coefficients {$$f_i$$} for these data, +defined by their multiplication by the matrix $$f_i = \sum_{j = 0}^{N - 1} D_{ij} t_j$$, where + +$$ +\begin{align*} +D_{ij} = +\begin{cases} +\sqrt{\frac{1}{N}} &(i = 0)\\ +\sqrt{\frac{2}{N}} \cos \left( \frac{\pi (2j + 1) i}{2 N} \right) &(1 \leq i \leq N - 1) +\end{cases} +\end{align*} +$$ + +### (c) + +{:.question} +Plot the inverse transform of the {$$f_i$$} by multiplying them by the inverse of the DCT matrix +(which is equal to its transpose) and verify that it matches the time series. + +### (d) + +{:.question} +Randomly sample and plot a subset of M points {$$t^\prime_k$$} of the {$$t_j$$}; you’ll later +investigate the dependence on the sample size. + +### (e) + +{:.question} +Starting with a random guess for the DCT coefficients {$$f^\prime_i$$}, use gradient descent to +minimize the error at the sample points + +$$ +\min_{\{f^\prime_i\}} \sum_{k = 0}^{M - 1} +\left( t^\prime_k - \sum_{j = 0}^{N - 1} D_{ij} f^\prime_i \right)^2 +$$ + +{:.question} +and plot the resulting estimated coefficients. + +### (f) + +{:.question} +The preceding minimization is under-constrained; it becomes well-posed if a norm of the DCT +coefficients is minimized subject to a constraint of agreeing with the sampled points. One of the +simplest (but not best [Gershenfeld, 1999]) ways to do this is by adding a penalty term to the +minimization. Repeat the gradient descent minimization using the L2 norm: + +$$ +\min_{\{f^\prime_i\}} \sum_{k = 0}^{M - 1} +\left( t^\prime_k - \sum_{j = 0}^{N - 1} D_{ij} f^\prime_i \right)^2 ++ \sum_{i = 0}^{N - 1} f^{\prime 2}_i +$$ + +{:.question} +and plot the resulting estimated coefficients. + +### (g) + +{:.question} +Repeat the gradient descent minimization using the L1 norm: + +$$ +\min_{\{f^\prime_i\}} \sum_{k = 0}^{M - 1} +\left( t^\prime_k - \sum_{j = 0}^{N - 1} D_{ij} f^\prime_i \right)^2 ++ \sum_{i = 0}^{N - 1} \vert f^{\prime}_i \vert +$$ + +{:.question} +Plot the resulting estimated coefficients, compare to the L2 norm estimate, and compare the +dependence of the results on M to the Nyquist sampling limit of twice the highest frequency. -- GitLab