More from Math Visualization
Other simulators in this category — or see all 61.
Kalman Filter (1-D)
Recursive optimal estimation: noisy measurements, hidden truth, predict + update with Q and R; random-walk or constant-velocity model with ±2σ band and innovations.
LMS / NLMS Adaptive Noise Cancellation
Primary p = s + v with v a fixed unknown FIR of Gaussian reference x[n]. Watch an L-tap FIR adapt by LMS or NLMS so error e = p − wᵀx → s; running MSE and ‖w − h‖.
DCT & JPEG Quantization (8×8)
64×64 luma: 8×8 DCT with −128 shift, ISO luminance quant table scaled by JPEG quality, or zigzag AC truncation (keep K). Click a block for coefficient heatmaps and zigzag trace.
PLL (Phase-Locked Loop)
Discrete-time analog-style PLL: multiplier PD e = K_d sin(φ_ref − φ_VCO), PI loop filter, VCO ω = ω_fr + K_v u; step ω_ref to explore lock, capture, and steady-state phase error.
ΔΣ (1-bit) Modulator
First- and second-order discrete-time ΔΣ with ±1 quantizer: shaped quantization noise, sine test tone, boxcar reconstruction, and Hann-windowed error spectrum (last 1024 samples).
Polyphase L/M Resampling
Zero-stuff by L, Hamming-windowed sinc FIR at the high rate with min(π/L,π/M) cutoff, then decimate by M; spectra in/out and Noble-identity polyphase intuition.