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61 lines
2.4 KiB
C
61 lines
2.4 KiB
C
#include "iir.h"
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void init_preemphasis(ResistorCapacitor *filter, float tau, float sample_rate, float ref_freq) {
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float dt = 1.0f / sample_rate;
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filter->alpha = tau / (tau + dt);
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float omega = M_2PI * ref_freq / sample_rate;
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filter->gain = 1.0f / sqrtf(1.0f + filter->alpha * filter->alpha - 2.0f * filter->alpha * cosf(omega));
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filter->prev_sample = 0.0f;
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}
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inline float apply_preemphasis(ResistorCapacitor *filter, float sample) {
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float out = (sample - filter->alpha * filter->prev_sample) * filter->gain;
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filter->prev_sample = sample;
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return out;
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}
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void tilt_init(TiltCorrectionFilter* filter, float correction_strength) {
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// This filter is a first-order IIR low-shelf filter.
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// The difference equation is: y[n] = b0*x[n] + b1*x[n-1] - a1*y[n-1]
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// We simplify it to y[n] = x[n] - a1*y[n-1] which acts as a leaky integrator.
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// The "correction_strength" is our leaky factor. It is the pole of the filter.
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// A value close to 1.0 places the pole very close to the unit circle,
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// providing a large boost to low frequencies (and DC).
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if (correction_strength >= 1.0f) {
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correction_strength = 0.99999f; // Prevent instability
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}
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filter->b0 = 1.0f;
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filter->b1 = 0.0f;
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filter->a1 = -correction_strength; // The feedback coefficient
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// Reset filter state
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filter->x_prev = 0.0f;
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filter->y_prev = 0.0f;
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}
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float tilt(TiltCorrectionFilter* filter, float input_sample) {
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// Apply the difference equation: y[n] = b0*x[n] + b1*x[n-1] - a1*y[n-1]
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float output_sample = filter->b0 * input_sample + filter->b1 * filter->x_prev - filter->a1 * filter->y_prev;
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// Important: Prevent output from running away due to DC offset accumulation
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// This is a simple guard. If the filter becomes unstable or the output
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// grows too large, it gets reset. For square waves, the absolute value of the
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// output should not significantly exceed the absolute value of the input.
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if (fabsf(output_sample) > 2.0f * fabsf(input_sample) && fabsf(input_sample) > 0.001f) {
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// This condition indicates the filter state might be diverging. Resetting it.
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// You may need to adjust the '2.0f' factor based on your signal.
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filter->y_prev = 0;
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output_sample = input_sample;
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}
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// Update the state for the next iteration
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filter->x_prev = input_sample;
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filter->y_prev = output_sample;
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return output_sample;
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} |