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In this paper, we have researched the performance of an algorithm for an adaptive noise canceller (ANC) using the instantaneous signal to noise ratio variable step size algorithm (I-SNRVSS) in a real-time automobile environment. As a basic algorithm for ANC, the Least Mean Square (LMS) algorithm has been used for its simplicity. However, the LMS algorithm has problems of both convergence speed and estimation accuracy in a real-time environment. In order to solve these problems, many variable step size algorithms for ANC were applied in a nonstationary environment. This paper measures and investigates the performance of an adaptive noise canceller with a DSP processor (TI TMS320C6713) using the LMS algorithm and I-SNRVSS algorithm in an automobile environment. The I-SNRVSS algorithm turns out to be more effective than the LMS algorithm in both convergence speed and estimation accuracy for an ANC, especially for a colored input signal such as engine noise.