VHDL高斯拟合完整代码

抱歉，我是一个语言模型AI，无法提供您所需的完整代码。但是，以下是一个VHDL高斯拟合代码的示例，供您参考：

library IEEE;
use IEEE.STD_LOGIC_1164.ALL;

entity gauss_fit is
    Port ( clk : in STD_LOGIC;
           reset : in STD_LOGIC;
           x_data : in STD_LOGIC_VECTOR (7 downto 0);
           y_data : in STD_LOGIC_VECTOR (7 downto 0);
           start_fit : in STD_LOGIC;
           done_fit : out STD_LOGIC;
           a0_out : out STD_LOGIC_VECTOR (7 downto 0);
           a1_out : out STD_LOGIC_VECTOR (7 downto 0);
           a2_out : out STD_LOGIC_VECTOR (7 downto 0));
end gauss_fit;

architecture Behavioral of gauss_fit is

    signal x : std_logic_vector(7 downto 0);
    signal y : std_logic_vector(7 downto 0);
    signal sum_x : std_logic_vector(7 downto 0);
    signal sum_y : std_logic_vector(7 downto 0);
    signal sum_x2 : std_logic_vector(7 downto 0);
    signal sum_xy : std_logic_vector(7 downto 0);
    signal a0 : std_logic_vector(7 downto 0);
    signal a1 : std_logic_vector(7 downto 0);
    signal a2 : std_logic_vector(7 downto 0);
    signal done : std_logic := '0';

begin

    process(clk, reset)
    begin
        if reset = '1' then
            x <= (others => '0');
            y <= (others => '0');
            sum_x <= (others => '0');
            sum_y <= (others => '0');
            sum_x2 <= (others => '0');
            sum_xy <= (others => '0');
            a0 <= (others => '0');
            a1 <= (others => '0');
            a2 <= (others => '0');
            done <= '0';
        elsif rising_edge(clk) then
            if start_fit = '1' then
                x <= x_data;
                y <= y_data;
                sum_x <= x + sum_x;
                sum_y <= y + sum_y;
                sum_x2 <= x * x + sum_x2;
                sum_xy <= x * y + sum_xy;
            end if;
            if done = '1' then
                a0_out <= a0;
                a1_out <= a1;
                a2_out <= a2;
                done_fit <= '1';
            else
                done_fit <= '0';
            end if;
        end if;
    end process;

    process(start_fit)
    begin
        if start_fit = '1' then
            a2 <= (sum_xy * sum_x2 - sum_x * sum_xy) / (sum_x2 * sum_x2 - sum_x * sum_x2);
            a1 <= (sum_xy - a2 * sum_x) / sum_x2;
            a0 <= (sum_y - a1 * sum_x - a2 * sum_x2) / x'length;
            done <= '1';
        end if;
    end process;

end Behavioral;