s_left_2 = conv(s_left_2,conv_t(5,:)); s_right_2 = conv(s_right_2,conv_t(5,:)); s_left_2 = s_left_2(1+wid:end-wid); s_right_2 = s_right_2(1+wid:end-wid); power_s = Count(s_left_2(1,:)); power_mult = power_s / power_xr; s_left_2 = s_left_2 / (power_mult)^0.5; s_right_2 = s_right_2 / (power_mult)^0.5;
时间: 2023-12-06 07:42:01 浏览: 28
这段代码看起来是对信号进行卷积、裁剪和归一化处理的过程。
首先,`conv` 函数对 `s_left_2` 和 `s_right_2` 进行卷积操作,`conv_t` 是卷积核。然后,信号 `s_left_2` 和 `s_right_2` 的两端各去掉 `wid` 个点,相当于将信号裁剪了一下。接着,计算 `s_left_2` 第一行元素的能量值 `power_s`,然后根据 `s_left_2` 的能量值与 `power_xr` 的比值,计算归一化系数 `power_mult`。最后,将 `s_left_2` 和 `s_right_2` 分别除以 `power_mult` 的平方根,进行归一化处理。
总之,这段代码的作用是对信号进行卷积、裁剪和归一化处理,以便后续的处理或分析。
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while(snr_t < 46 ) %迭代训练 s_left_0 = [fill,soud_left_d,fill]; s_right_0 = [fill,soud_right_d,fill]; s_left_1 = ResBlock(s_left_0,conv_t(2,:),conv_t(3,:)); s_right_1 = ResBlock(s_right_0,conv_t(2,:),conv_t(3,:)); s_left_1 = conv(s_left_1,conv_t(4,:)); s_right_1 = conv(s_right_1,conv_t(4,:)); s_left_2 = s_left_0(1+wid:end-wid) + s_left_1(1+4*wid:end-4*wid) * w_t; s_right_2 = s_right_0(1+wid:end-wid) + s_right_1(1+4*wid:end-4*wid) * w_t; s_left_2 = PixelShuffle(s_left_2,conv_t(6:21,:)); s_right_2 = PixelShuffle(s_right_2,conv_t(6:21,:)); s_left_2 = conv(s_left_2,conv_t(5,:)); s_right_2 = conv(s_right_2,conv_t(5,:)); s_left_2 = s_left_2(1+wid:end-wid); s_right_2 = s_right_2(1+wid:end-wid); power_s = Count(s_left_2(1,:)); power_mult = power_s / power_xr; s_left_2 = s_left_2 / (power_mult)^0.5; s_right_2 = s_right_2 / (power_mult)^0.5; temp = s_left_2 - soud_left_t; loss_num = LossCount(temp,soud_left); diff = Variance(temp,soud_left); snr = psnr(temp,soud_left);
这段代码是一个音频处理的迭代训练过程。具体来说,它包括以下几个步骤:
1. 初始化输入信号,其中 soud_left_d 和 soud_right_d 是左右声道的音频数据;
2. 使用 ResBlock 函数对输入信号进行残差块处理;
3. 对处理后的信号进行卷积操作,并加上一个权重 w_t,得到 s_left_2 和 s_right_2;
4. 对 s_left_2 和 s_right_2 进行像素洗牌(PixelShuffle)操作;
5. 再次对洗牌后的信号进行卷积操作;
6. 对信号进行归一化处理,使得其功率与参考信号 power_xr 相同;
7. 计算残差和损失,以及信噪比(SNR)。
整个过程会不断迭代,直到 SNR 达到一定阈值(46)。这种音频处理技术可以用于语音增强、降噪等方面。
while(snr_t < 46 ) %迭代训练 % s_left_0 = conv(soud_left_d,conv_t(1,:)); % s_right_0 = conv(soud_right_d,conv_t(1,:)); s_left_0 = [fill,soud_left_d,fill]; s_right_0 = [fill,soud_right_d,fill]; s_left_1 = ResBlock(s_left_0,conv_t(2,:),conv_t(3,:)); s_right_1 = ResBlock(s_right_0,conv_t(2,:),conv_t(3,:)); s_left_1 = conv(s_left_1,conv_t(4,:)); s_right_1 = conv(s_right_1,conv_t(4,:));
这段代码是用于迭代训练的,其中的`while`循环条件是当信噪比`snr_t`小于46时执行。接下来的代码中,首先使用`conv_t(1,:)`对左右声道的信号进行卷积操作,并将结果存储到`s_left_0`和`s_right_0`变量中。然后,在`s_left_0`和`s_right_0`两个变量的首尾分别添加`fill`填充值。接着,调用`ResBlock`函数对`s_left_0`和`s_right_0`进行残差块处理,得到`s_left_1`和`s_right_1`。最后,再次对`s_left_1`和`s_right_1`进行卷积操作,并将结果存储到`s_left_1`和`s_right_1`变量中。