RF Filter Monte Carlo Analysis
Analyse how component tolerances affect your filter's passband ripple and stopband rejection. Run thousands of Monte Carlo trials to get yield and worst-case statistics.
How It Works
Monte Carlo analysis evaluates how real-world component tolerances affect filter performance. Instead of assuming ideal values, each trial randomly perturbs every capacitor and inductor within its tolerance band, simulates the filter response, and records key metrics.
Over hundreds or thousands of trials, you get statistical distributions of passband ripple, -3 dB cutoff shift, and stopband rejection. The yield — the percentage of trials meeting your spec — directly predicts manufacturing success rate.
Two distribution models are supported: uniform (every value within the tolerance range is equally likely — worst-case analysis) and Gaussian (values cluster around nominal with 3σ equal to the stated tolerance — more realistic for precision components).
The tool synthesises Butterworth (maximally flat) or Chebyshev Type I (equiripple passband) LC ladder filters, then runs the Monte Carlo sweep using exact ABCD matrix chain multiplication for accuracy.
Related Calculators
FAQ
How many Monte Carlo trials do I need?+
For a rough yield estimate, 200-500 trials suffice. For accurate tail statistics (e.g. worst-case at 99.7% confidence), use 2,000-10,000 trials. The free tier supports up to 500; upgrade to Pro for up to 10,000.
Uniform vs Gaussian distribution — which should I use?+
Use uniform for worst-case analysis (every value in the tolerance range is equally likely). Use Gaussian when your components are precision-graded — values cluster near nominal, with outliers rare. Gaussian typically yields higher pass rates for the same tolerance.
Why does my Chebyshev filter show worse yield than Butterworth?+
Chebyshev filters have sharper rolloff but rely on precise ripple levels in the passband. Component variations directly distort the equiripple response, causing some trials to exceed the ripple spec. Butterworth filters are more tolerant because their passband is monotonically flat.
What metrics are reported?+
Each trial records: passband ripple (dB), -3 dB cutoff frequency, minimum stopband rejection (dB), and insertion loss at DC. The results show mean, standard deviation, min/max, and yield percentage against your target specifications.