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Real-time implementation of Maximum a Posteriori (MAP) based noise reductions using Leon 3 System on Chip

机译:基于Leon 3系统的基于后验(MAP)的噪声减少的实时实现使用芯片

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Maximum a Posteriori (MAP) is an advance method to estimate noise for various audio noise reduction applications. MAP algorithm with variable speech distribution involves complex and intensive computation. Implementation in nai?ve method can't achieve real-time constraint. This paper proposed a method to optimize the MAP algorithm with variable speech distribution in software implementation for System on Chip (SoC). System utilizes Leon 3 microprocessor as main processing system. System is implemented in software hardware co-design to ensure flexibility and reduce computational time burden. Optimization has been done by replacing some arithmetic function with approximation function and by giving optimization option in the compiler. The simulation results show that the optimized MAP algorithm produces a linear result in SNR enhancement and faster computation time under time budget constraint.
机译:最大后验(MAP)是用于估计各种音频降噪应用的噪声的预先方法。 具有可变语音分布的地图算法涉及复杂和密集的计算。 NAI ve方法的实现无法达到实时约束。 本文提出了一种在芯片(SOC)系统中具有可变语音分布的地图算法的方法。 系统利用莱昂3微处理器作为主处理系统。 系统是在软件硬件共同设计中实现的,以确保灵活性并降低计算时负担。 通过替换具有近似函数的一些算术函数以及编译器中的优化选项来完成优化。 仿真结果表明,优化的地图算法在时间预算约束下产生了SNR增强和更快的计算时间的线性结果。

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