chatGPT 程序员-----FFT代码的生成和验证（代号HZQ游戏）

chatGPT 程序员-----FFT代码的生成和验证

中国在这波AI热潮中不能落伍！Chat GPT突然掀起的这波AI新高潮，令各国各界各大公司竟然措手不及！虽然对于Chat GPT聊天对话智慧、书写文案水平等有过度夸张炒作之嫌疑，但是Chat GPT此前通过了美国医师执照考试、律师资格考试、工商管理硕士运营考试！业界直呼“知识型员工应该非常担心自己的岗位了！”Chat GPT“ 考过这三个准入资格是实实在在的。

下面我们就用这个chatGPT开始编程之旅，首先我们用chatGPT完成FFT代码的编程和测试，首先是将chatGPT生成的代码在Matlab中进行验证（下一节将再利用生的代码转为C 代码在平台上进行研证）。

第一步我们首先让chatGPT为我们生成FFT的代码，代码将限定从一个频率到另一个特定频率的数据进行检查，这样将降低CPU的使用率，对于在部分资源有限的平台上跑FFT算法是非常有益的：

The function takes four arguments: signal is the input signal, fs is the sampling frequency, f1 is the lower frequency bound, and f2 is the upper frequency bound. It returns two output variables: freq is the frequency vector between f1 and f2, and mag is the magnitude spectrum of the signal between f1 and f2.

The function works by computing the one-sided FFT of the signal using the built-in fft function, and then extracting the frequency and magnitude vectors between f1 and f2. It returns these vectors as output variables.

You can call this function from your own MATLAB code to compute the FFT of a signal between a lower and upper frequency bound, like this:

% Generate test signal fs = 1000; % Sampling frequency t = 0:1/fs:1-1/fs; % Time vector f1 = 40; % Lower frequency bound f2 = 120; % Upper frequency bound signal = sin(2*pi*50*t) 0.5*sin(2*pi*100*t) 0.2*randn(size(t)); % Signal with noise % Compute FFT between f1 and f2 [freq, mag] = fft_between_freqs(signal, fs, f1, f2); % Plot the magnitude spectrum plot(freq, mag); xlabel('Frequency (Hz)'); ylabel('Magnitude'); title(sprintf('FFT between %d and %d Hz', f1, f2));

In this example, the function is called with a test signal consisting of a sine wave with frequency 50 Hz and a noisy sine wave with frequency 100 Hz, with a sampling rate of 1000 Hz. The function is asked to compute the FFT between 40 and 120 Hz, and the resulting magnitude spectrum is plotted.