我有多少的FFT每秒可以做我的智能手机？ （用于执行语音识别） [英] How many FFTs per second can I do on my smartphone? (for performing voice recognition)
问题描述
我探索语音识别和DSP，所以我想实现我的智能手机一个简单的声音频率分析仪（我同时拥有一部iPhone和三星Nexus S运行Android）。我曾在Matlab previously完成基本的DSP。
I'm exploring voice recognition and DSP, and so I would like to implement a simple sound frequency analyzer on my smartphone (I have both an iPhone and a Samsung Nexus S running Android). I have done basic DSP in Matlab previously.
这是我的理解，我需要执行FFT获得信号的基频。
From my understanding, I need to perform an FFT to get the fundamental frequencies of a signal.
所以，现在，我想品尝麦克风44100赫兹。如果我使用的样本量512的滑动窗口重叠50％，这意味着我需要做的FFT每256个样品，或0.00580秒。
So now, I would like to sample the microphone at 44100 Hz. If I use a sliding window of sample size 512 with 50% overlap, that means I need to do an FFT every 256 samples, or 0.00580 seconds.
那速度似乎非常高，尤其是如果我计划在Java中为Android。请问我的智能手机能够处理的速度？据我所知，您可以在C / C ++的Android程序，但我想与Java保持它暂且。
That rate seems really high, particularly if I program in Java for Android. Will my smartphone be able to handle that speed? I am aware that you can program in C/C++ on Android, but I would like to keep it with Java for the time being.
推荐答案
执行实数到复数FFT需要约5/2 N LG电子ñ浮点运算（加法和乘法）。在你的情况下，N = 512，那么：
Performing a real-to-complex FFT requires ~5/2 n lg n floating-point operations (additions and multiplications). In your case, n=512, so:
flops per fft ~= (5/2) * 512 * 9 = 11520
所以，每秒172的FFT需要每秒200万次浮点运算。这听起来好像很多，但它确实是没有那么多。典型的ARMv7级智能手机的硬件能够数亿或数十亿次浮点运算每秒的。
So 172 ffts per second requires about 2 million floating-point operations per second. That sounds like a lot, but it really isn't that many. The hardware of a typical armv7-class smartphone is capable of hundreds of millions or billions of floating-point operations per second.
但是请注意，你会希望有一个精心编写高性能的FFT;写得不好的FFT非常费电。在iPhone上，你可以使用加速架构（内置于操作系统，并提供了SDK），它提供了一个很好的一套FFT功能;我不知道什么是在Android。
Note however that you will want to have a carefully-written high-performance FFT; poorly written FFTs are notoriously inefficient. On the iPhone, you can use the Accelerate framework (built right into the OS, and available in the SDK), which provides a nice set of FFT functions; I'm not sure what's available on Android.
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