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Фильтр нижних частот и верхних частот в С#

Мне нужен фильтр низких и высоких частот, написанный на С#. У меня есть два массива для этого процесса фильтрации. Я думаю, что если я попытаюсь преобразовать алгоритмы Matlab Butterworth и Chebyshev в С#, было бы проще. Но я не мог найти код butter.m и чебышевских алгоритмов в Интернете, и я не хочу настраивать набор инструментов Matlab и обработки сигналов на свой компьютер. Не могли бы вы предоставить эти коды, пожалуйста? Спасибо..

4b9b3361

Ответ 1

http://www.musicdsp.org/archive.php?classid=3#38

Я реализовал фильтр в полукоде выше, как описано в нашем программном обеспечении sEMG, и он отлично работает.

public class FilterButterworth
{
    /// <summary>
    /// rez amount, from sqrt(2) to ~ 0.1
    /// </summary>
    private readonly float resonance;

    private readonly float frequency;
    private readonly int sampleRate;
    private readonly PassType passType;

    private readonly float c, a1, a2, a3, b1, b2;

    /// <summary>
    /// Array of input values, latest are in front
    /// </summary>
    private float[] inputHistory = new float[2];

    /// <summary>
    /// Array of output values, latest are in front
    /// </summary>
    private float[] outputHistory = new float[3];

    public FilterButterworth(float frequency, int sampleRate, PassType passType, float resonance)
    {
        this.resonance = resonance;
        this.frequency = frequency;
        this.sampleRate = sampleRate;
        this.passType = passType;

        switch (passType)
        {
            case PassType.Lowpass:
                c = 1.0f / (float)Math.Tan(Math.PI * frequency / sampleRate);
                a1 = 1.0f / (1.0f + resonance * c + c * c);
                a2 = 2f * a1;
                a3 = a1;
                b1 = 2.0f * (1.0f - c * c) * a1;
                b2 = (1.0f - resonance * c + c * c) * a1;
                break;
            case PassType.Highpass:
                c = (float)Math.Tan(Math.PI * frequency / sampleRate);
                a1 = 1.0f / (1.0f + resonance * c + c * c);
                a2 = -2f * a1;
                a3 = a1;
                b1 = 2.0f * (c * c - 1.0f) * a1;
                b2 = (1.0f - resonance * c + c * c) * a1;
                break;
        }
    }

    public enum PassType
    {
        Highpass,
        Lowpass,
    }

    public void Update(float newInput)
    {
        float newOutput = a1 * newInput + a2 * this.inputHistory[0] + a3 * this.inputHistory[1] - b1 * this.outputHistory[0] - b2 * this.outputHistory[1];

        this.inputHistory[1] = this.inputHistory[0];
        this.inputHistory[0] = newInput;

        this.outputHistory[2] = this.outputHistory[1];
        this.outputHistory[1] = this.outputHistory[0];
        this.outputHistory[0] = newOutput;
    }

    public float Value
    {
        get { return this.outputHistory[0]; }
    }
}

Ответ 2

Я нашел этот онлайн-инструмент, который выглядит многообещающим: Интерактивный дизайн цифрового фильтра: фильтры Butterworth/Bessel/Chebyshev

Вы просто вводите свои требования:

  • Дизайн фильтра: Баттерворт/Бессел/Чебышев
  • Тип фильтра: Lowpass/Highpass/Bandpass/Bandstop
  • Порядок фильтрации
  • Угловая частота/частоты

Нажмите "Отправить", и он вычислит следующую информацию:

  • Усиления, полюса, нули
  • Отношение повторения
  • C-код, реализующий рекуррентное отношение
  • Графики амплитудных, фазовых, импульсных и шаговых ответов

Вы можете реализовать фильтр в С# непосредственно из отношения рекурсии.

Если вам нужны только несколько постоянных фильтров, все готово. Однако, если вам нужно настроить параметры фильтра во время выполнения, вам нужно будет сделать больше. К счастью, профессор предоставил исходный код для своего инструмента, и его можно было бы преобразовать в С#.

Ответ 3

Вы можете посмотреть исходный код фильтра Butterworth Low Pass здесь в другом вопросе stackoverflow. Как отмечают другие, EmguCV поставляется с множеством фильтров, которые эффективно кодируются и доступны из коробки.

Ответ 4

Посмотрите OpenCV/EmguCV.

Они оба с открытым исходным кодом, поэтому вы можете иметь "код", если это то, что вы ищете.

Ответ 5

Вот некоторые примеры кода С# butterworth и chebyshev, используя NMath fft.

Ответ 7

здесь он имеет много режимов, пик HP LP BP и т.д., это BiQuad, возможно, 2-полюсный статический фильтр, что-то вроде этого, это особый фильтр и имеет определенный цифровой результат: https://github.com/filoe/cscore/blob/master/CSCore/DSP/BiQuad.cs

    /*
     * These implementations are based on http://www.earlevel.com/main/2011/01/02/biquad-formulas/
     */

    using System;

    namespace CSCore.DSP
    {
        /// <summary>
        /// Represents a biquad-filter.
        /// </summary>
        public abstract class BiQuad
        {
            /// <summary>
            /// The a0 value.
            /// </summary>
            protected double A0;
            /// <summary>
            /// The a1 value.
            /// </summary>
            protected double A1;
            /// <summary>
            /// The a2 value.
            /// </summary>
            protected double A2;
            /// <summary>
            /// The b1 value.
            /// </summary>
            protected double B1;
            /// <summary>
            /// The b2 value.
            /// </summary>
            protected double B2;
            /// <summary>
            /// The q value.
            /// </summary>
            private double _q;
            /// <summary>
            /// The gain value in dB.
            /// </summary>
            private double _gainDB;
            /// <summary>
            /// The z1 value.
            /// </summary>
            protected double Z1;
            /// <summary>
            /// The z2 value.
            /// </summary>
            protected double Z2;

            private double _frequency;

            /// <summary>
            /// Gets or sets the frequency.
            /// </summary>
            /// <exception cref="System.ArgumentOutOfRangeException">value;The samplerate has to be bigger than 2 * frequency.</exception>
            public double Frequency
            {
                get { return _frequency; }
                set
                {
                    if (SampleRate < value * 2)
                    {
                        throw new ArgumentOutOfRangeException("value", "The samplerate has to be bigger than 2 * frequency.");
                    }
                    _frequency = value;
                    CalculateBiQuadCoefficients();
                }
            }

            /// <summary>
            /// Gets the sample rate.
            /// </summary>
            public int SampleRate { get; private set; }

            /// <summary>
            /// The q value.
            /// </summary>
            public double Q
            {
                get { return _q; }
                set
                {
                    if (value <= 0)
                    {
                        throw new ArgumentOutOfRangeException("value");
                    }
                    _q = value;
                    CalculateBiQuadCoefficients();
                }
            }

            /// <summary>
            /// Gets or sets the gain value in dB.
            /// </summary>
            public double GainDB
            {
                get { return _gainDB; }
                set
                {
                    _gainDB = value;
                    CalculateBiQuadCoefficients();
                }
            }

            /// <summary>
            /// Initializes a new instance of the <see cref="BiQuad"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The frequency.</param>
            /// <exception cref="System.ArgumentOutOfRangeException">
            /// sampleRate
            /// or
            /// frequency
            /// or
            /// q
            /// </exception>
            protected BiQuad(int sampleRate, double frequency)
                : this(sampleRate, frequency, 1.0 / Math.Sqrt(2))
            {
            }

            /// <summary>
            /// Initializes a new instance of the <see cref="BiQuad"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The frequency.</param>
            /// <param name="q">The q.</param>
            /// <exception cref="System.ArgumentOutOfRangeException">
            /// sampleRate
            /// or
            /// frequency
            /// or
            /// q
            /// </exception>
            protected BiQuad(int sampleRate, double frequency, double q)
            {
                if (sampleRate <= 0)
                    throw new ArgumentOutOfRangeException("sampleRate");
                if (frequency <= 0)
                    throw new ArgumentOutOfRangeException("frequency");
                if (q <= 0)
                    throw new ArgumentOutOfRangeException("q");
                SampleRate = sampleRate;
                Frequency = frequency;
                Q = q;
                GainDB = 6;
            }

            /// <summary>
            /// Processes a single <paramref name="input"/> sample and returns the result.
            /// </summary>
            /// <param name="input">The input sample to process.</param>
            /// <returns>The result of the processed <paramref name="input"/> sample.</returns>
            public float Process(float input)
            {
                double o = input * A0 + Z1;
                Z1 = input * A1 + Z2 - B1 * o;
                Z2 = input * A2 - B2 * o;
                return (float)o;
            }

            /// <summary>
            /// Processes multiple <paramref name="input"/> samples.
            /// </summary>
            /// <param name="input">The input samples to process.</param>
            /// <remarks>The result of the calculation gets stored within the <paramref name="input"/> array.</remarks>
            public void Process(float[] input)
            {
                for (int i = 0; i < input.Length; i++)
                {
                    input[i] = Process(input[i]);
                }
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected abstract void CalculateBiQuadCoefficients();
        }

        /// <summary>
        /// Used to apply a lowpass-filter to a signal.
        /// </summary>
        public class LowpassFilter : BiQuad
        {
            /// <summary>
            /// Initializes a new instance of the <see cref="LowpassFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The filter corner frequency.</param>
            public LowpassFilter(int sampleRate, double frequency)
                : base(sampleRate, frequency)
            {
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                var norm = 1 / (1 + k / Q + k * k);
                A0 = k * k * norm;
                A1 = 2 * A0;
                A2 = A0;
                B1 = 2 * (k * k - 1) * norm;
                B2 = (1 - k / Q + k * k) * norm;
            }
        }

        /// <summary>
        /// Used to apply a highpass-filter to a signal.
        /// </summary>
        public class HighpassFilter : BiQuad
        {
            private int p1;
            private double p2;

            /// <summary>
            /// Initializes a new instance of the <see cref="HighpassFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The filter corner frequency.</param>
            public HighpassFilter(int sampleRate, double frequency) 
                : base(sampleRate, frequency)
            {
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                var norm = 1 / (1 + k / Q + k * k);
                A0 = 1 * norm;
                A1 = -2 * A0;
                A2 = A0;
                B1 = 2 * (k * k - 1) * norm;
                B2 = (1 - k / Q + k * k) * norm;
            }
        }

        /// <summary>
        /// Used to apply a bandpass-filter to a signal.
        /// </summary>
        public class BandpassFilter : BiQuad
        {
            /// <summary>
            /// Initializes a new instance of the <see cref="BandpassFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The filter corner frequency.</param>
            public BandpassFilter(int sampleRate, double frequency) 
                : base(sampleRate, frequency)
            {
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                double norm = 1 / (1 + k / Q + k * k);
                A0 = k / Q * norm;
                A1 = 0;
                A2 = -A0;
                B1 = 2 * (k * k - 1) * norm;
                B2 = (1 - k / Q + k * k) * norm;
            }
        }

        /// <summary>
        /// Used to apply a notch-filter to a signal.
        /// </summary>
        public class NotchFilter : BiQuad
        {
            /// <summary>
            /// Initializes a new instance of the <see cref="NotchFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The filter corner frequency.</param>
            public NotchFilter(int sampleRate, double frequency) 
                : base(sampleRate, frequency)
            {
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                double norm = 1 / (1 + k / Q + k * k);
                A0 = (1 + k * k) * norm;
                A1 = 2 * (k * k - 1) * norm;
                A2 = A0;
                B1 = A1;
                B2 = (1 - k / Q + k * k) * norm;
            }
        }

        /// <summary>
        /// Used to apply a lowshelf-filter to a signal.
        /// </summary>
        public class LowShelfFilter : BiQuad
        {
            /// <summary>
            /// Initializes a new instance of the <see cref="LowShelfFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The filter corner frequency.</param>
            /// <param name="gainDB">Gain value in dB.</param>
            public LowShelfFilter(int sampleRate, double frequency, double gainDB) 
                : base(sampleRate, frequency)
            {
                GainDB = gainDB;
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                const double sqrt2 = 1.4142135623730951;
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                double v = Math.Pow(10, Math.Abs(GainDB) / 20.0);
                double norm;
                if (GainDB >= 0)
                {    // boost
                    norm = 1 / (1 + sqrt2 * k + k * k);
                    A0 = (1 + Math.Sqrt(2 * v) * k + v * k * k) * norm;
                    A1 = 2 * (v * k * k - 1) * norm;
                    A2 = (1 - Math.Sqrt(2 * v) * k + v * k * k) * norm;
                    B1 = 2 * (k * k - 1) * norm;
                    B2 = (1 - sqrt2 * k + k * k) * norm;
                }
                else
                {    // cut
                    norm = 1 / (1 + Math.Sqrt(2 * v) * k + v * k * k);
                    A0 = (1 + sqrt2 * k + k * k) * norm;
                    A1 = 2 * (k * k - 1) * norm;
                    A2 = (1 - sqrt2 * k + k * k) * norm;
                    B1 = 2 * (v * k * k - 1) * norm;
                    B2 = (1 - Math.Sqrt(2 * v) * k + v * k * k) * norm;
                }
            }
        }

        /// <summary>
        /// Used to apply a highshelf-filter to a signal.
        /// </summary>
        public class HighShelfFilter : BiQuad
        {
            /// <summary>
            /// Initializes a new instance of the <see cref="HighShelfFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sample rate.</param>
            /// <param name="frequency">The filter corner frequency.</param>
            /// <param name="gainDB">Gain value in dB.</param>
            public HighShelfFilter(int sampleRate, double frequency, double gainDB)
                : base(sampleRate, frequency)
            {
                GainDB = gainDB;
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                const double sqrt2 = 1.4142135623730951;
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                double v = Math.Pow(10, Math.Abs(GainDB) / 20.0);
                double norm;
                if (GainDB >= 0)
                {    // boost
                    norm = 1 / (1 + sqrt2 * k + k * k);
                    A0 = (v + Math.Sqrt(2 * v) * k + k * k) * norm;
                    A1 = 2 * (k * k - v) * norm;
                    A2 = (v - Math.Sqrt(2 * v) * k + k * k) * norm;
                    B1 = 2 * (k * k - 1) * norm;
                    B2 = (1 - sqrt2 * k + k * k) * norm;
                }
                else
                {    // cut
                    norm = 1 / (v + Math.Sqrt(2 * v) * k + k * k);
                    A0 = (1 + sqrt2 * k + k * k) * norm;
                    A1 = 2 * (k * k - 1) * norm;
                    A2 = (1 - sqrt2 * k + k * k) * norm;
                    B1 = 2 * (k * k - v) * norm;
                    B2 = (v - Math.Sqrt(2 * v) * k + k * k) * norm;
                }
            }
        }

        /// <summary>
        /// Used to apply an peak-filter to a signal.
        /// </summary>
        public class PeakFilter : BiQuad
        {
            /// <summary>
            /// Gets or sets the bandwidth.
            /// </summary>
            public double BandWidth
            {
                get { return Q; }
                set
                {
                    if (value <= 0)
                        throw new ArgumentOutOfRangeException("value");
                    Q = value;
                }
            }

            /// <summary>
            /// Initializes a new instance of the <see cref="PeakFilter"/> class.
            /// </summary>
            /// <param name="sampleRate">The sampleRate of the audio data to process.</param>
            /// <param name="frequency">The center frequency to adjust.</param>
            /// <param name="bandWidth">The bandWidth.</param>
            /// <param name="peakGainDB">The gain value in dB.</param>
            public PeakFilter(int sampleRate, double frequency, double bandWidth, double peakGainDB)
                : base(sampleRate, frequency, bandWidth)
            {
                GainDB = peakGainDB;
            }

            /// <summary>
            /// Calculates all coefficients.
            /// </summary>
            protected override void CalculateBiQuadCoefficients()
            {
                double norm;
                double v = Math.Pow(10, Math.Abs(GainDB) / 20.0);
                double k = Math.Tan(Math.PI * Frequency / SampleRate);
                double q = Q;

                if (GainDB >= 0) //boost
                {
                    norm = 1 / (1 + 1 / q * k + k * k);
                    A0 = (1 + v / q * k + k * k) * norm;
                    A1 = 2 * (k * k - 1) * norm;
                    A2 = (1 - v / q * k + k * k) * norm;
                    B1 = A1;
                    B2 = (1 - 1 / q * k + k * k) * norm;
                }
                else //cut
                {
                    norm = 1 / (1 + v / q * k + k * k);
                    A0 = (1 + 1 / q * k + k * k) * norm;
                    A1 = 2 * (k * k - 1) * norm;
                    A2 = (1 - 1 / q * k + k * k) * norm;
                    B1 = A1;
                    B2 = (1 - v / q * k + k * k) * norm;
                }
            }
        }
    }