VHDLで理解しやすい10の移動平均実装コード

entity MovingAverage is
    Port ( clk : in  STD_LOGIC;
           data_in : in  INTEGER;
           avg_out : out  INTEGER);
end MovingAverage;

architecture Behavioral of MovingAverage is
    signal sum : INTEGER := 0;
    signal data_array : INTEGER_VECTOR(0 to 4) := (others => 0);
begin
    process(clk)
    begin
        if rising_edge(clk) then
            sum <= sum - data_array(0) + data_in;
            data_array <= data_array(1 to 4) & data_in;
            avg_out <= sum / 5;
        end if;
    end process;
end Behavioral;

-- コードの内容はサンプルコード1と似ていますが、data_arrayのサイズと除算の数値が異なります。
-- 上記のサンプルコードを参考に、適切な変更を加えてください。

library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;

entity SecondOrderMovingAverage is
    Port ( clk : in STD_LOGIC;
           data_in : in STD_LOGIC_VECTOR(7 downto 0);
           avg_out : out STD_LOGIC_VECTOR(7 downto 0));
end SecondOrderMovingAverage;

architecture Behavioral of SecondOrderMovingAverage is
    signal temp_avg : STD_LOGIC_VECTOR(7 downto 0);
    signal data_buffer : array(0 to 9) of STD_LOGIC_VECTOR(7 downto 0) := (others => (others => '0'));
begin
    process(clk)
    variable sum1 : integer := 0;
    variable sum2 : integer := 0;
    begin
        if rising_edge(clk) then
            for i in 0 to 8 loop
                data_buffer(i) <= data_buffer(i+1);
            end loop;
            data_buffer(9) <= data_in;

            -- 一次移動平均
            sum1 := 0;
            for i in 0 to 9 loop
                sum1 := sum1 + conv_integer(data_buffer(i));
            end loop;
            temp_avg <= conv_std_logic_vector(sum1/10, 8);

            -- 二次移動平均
            sum2 := (sum1 + conv_integer(temp_avg)) / 2;
            avg_out <= conv_std_logic_vector(sum2, 8);
        end if;
    end process;
end Behavioral;

-- ノイズ除去のための移動平均を計算するモジュール
module NoiseReduction(signal_in, signal_out);
  input signal_in;
  output signal_out;
  variable sum: real;
  constant window_size: integer := 5;
  -- 移動平均計算
  for i in 1 to window_size loop
    sum := sum + signal_in(i);
  end loop;
  signal_out := sum / window_size;
end module;

-- 信号のピークを検出するモジュール
module PeakDetection(signal_in, peak_value);
  input signal_in;
  output peak_value;
  variable max_val: real := 0.0;
  -- ピーク検出
  for i in 1 to signal_in'length loop
    if signal_in(i) > max_val then
      max_val := signal_in(i);
    end if;
  end loop;
  peak_value := max_val;
end module;

-- 信号の平滑化を行うモジュール
module SignalSmoothing(signal_in, smoothed_signal);
  input signal_in;
  output smoothed_signal;
  variable sum: real;
  constant window_size: integer := 3;
  -- 平滑化処理
  for i in 1 to window_size loop
    sum := sum + signal_in(i);
  end loop;
  smoothed_signal := sum / window_size;
end module;

-- トレンド分析のための移動平均を計算するモジュール
module TrendAnalysis(signal_in, trend_value);
  input signal_in;
  output trend_value;
  variable sum: real;
  constant window_size: integer := 10;
  -- トレンド計算
  for i in 1 to window_size loop
    sum := sum + signal_in(i);
  end loop;
  if (sum / window_size) > signal_in(window_size) then
    trend_value := "UP";
  else
    trend_value := "DOWN";
  end if;
end module;

-- 周期的なデ

ータを分析するためのモジュール
module PeriodicDataAnalysis(signal_in, periodic_value);
  input signal_in;
  output periodic_value;
  variable sum: real;
  constant window_size: integer := 20;
  -- 周期的データの分析
  for i in 1 to window_size loop
    sum := sum + signal_in(i);
  end loop;
  periodic_value := sum / window_size;
end module;

-- データ流の予測を行うモジュール
module DataFlowPrediction(signal_in, predicted_value);
  input signal_in;
  output predicted_value;
  variable sum_past: real;
  variable sum_recent: real;
  constant window_size: integer := 10;
  -- 過去のデータと最近のデータを基に予測
  for i in 1 to window_size/2 loop
    sum_past := sum_past + signal_in(i);
  end loop;
  for i in (window_size/2)+1 to window_size loop
    sum_recent := sum_recent + signal_in(i);
  end loop;
  if sum_recent > sum_past then
    predicted_value := "INCREASE";
  else
    predicted_value := "DECREASE";
  end if;
end module;

-- 移動平均の計算中に桁溢れが発生するリスクがある例
module RiskOfOverflow(signal_in, average_out);
  input signal_in : std_logic_vector(7 downto 0);
  output average_out : std_logic_vector(7 downto 0);
  variable sum: integer;
  constant window_size: integer := 10;

  -- 移動平均の計算
  for i in 1 to window_size loop
    sum := sum + to_integer(unsigned(signal_in(i)));
  end loop;

  average_out := std_logic_vector(to_unsigned(sum/window_size, 8));
end module;

-- 移動平均の計算中に浮動小数点の精度が問題となる例
module FloatingPointPrecision(signal_in, average_out);
  input signal_in : real;
  output average_out : real;
  variable sum: real;
  constant window_size: integer := 10;

  -- 移動平均の計算
  for i in 1 to window_size loop
    sum := sum + signal_in(i);
  end loop;

  average_out := sum / window_size;
end module;

-- 大きなウィンドウサイズを持つ移動平均の例
module LargeWindowSize(signal_in, average_out);
  input signal_in : std_logic_vector(15 downto 0);
  output average_out : std_logic_vector(15 downto 0);
  variable sum: integer;
  constant window_size: integer := 100;

  -- 移動平均の計算
  for i in 1 to window_size loop
    sum := sum + to_integer(unsigned(signal_in(i)));
  end loop;

  average_out := std_logic_vector(to_unsigned(sum/window_size, 16));
end module;

library IEEE;
use IEEE.STD_LOGIC_1164.ALL;
use IEEE.STD_LOGIC_ARITH.ALL;
use IEEE.STD_LOGIC_UNSIGNED.ALL;

entity EMA is
    Port ( data_in : in  STD_LOGIC_VECTOR(7 downto 0);
           alpha : in STD_LOGIC_VECTOR(7 downto 0);  -- 重みの係数
           ema_out : out STD_LOGIC_VECTOR(7 downto 0));
end EMA;

architecture Behavioral of EMA is
    signal prev_ema : STD_LOGIC_VECTOR(7 downto 0) := "00000000";
begin
    process(data_in, alpha, prev_ema)
    begin
        ema_out <= (alpha * data_in + (256 - alpha) * prev_ema) / 256;
        prev_ema <= ema_out;
    end process;
end Behavioral;