To design, implement and test a lossless compression/decompression tool for digital audio. This technique is used to reduce the digital data that has to be transmitted over the communications channel. The implementation can be done on the FPGA or DSP boards. The paper attached proposes a solution to code digital audio signal in such a way that data is not lost during compression. The algorithm uses prediction techniques to aid compression. A report which includes i) A description of the implementation. ii) Commented programme listings. iii) The testing procedures adopted (with results) to ensure the proper operation. iv) Results summarising the performance of the algorithm. v) Comments regarding the efficiency of your implementation; vi) Comments on the techniques used and the results obtained. Possible improvements to your system should also be discussed. A demonstration in the lab together with a short discussion is expected. Only one report is required per group (of two students), with the names of both students included. It is expected that the work is shared equally between both members of the group. Abstract-This paper proposes a cascaded RLS-LMS predictor for lossless audio coding. In this proposed predictor, a high-order LMS predictor is employed to model the ample tonal and harmonic components of the audio signal for optimal prediction gain performance. To solve the slow convergence problem of the LMS algorithm with colored inputs, a low-order RLS predictor is cascaded prior to the LMS predictor to remove the spectral tilt of the audio signal. This cascaded RLS-LMS structure effectively mitigates the slow convergence problem of the LMS algorithm and provides superior prediction gain performance compared with the conventional LMS predictor, resulting in a better overall compression performance.
To solve the slow convergence problem of the LMS algorithm, a low-order RLS predictor is cascaded prior to the LMS predictor in REF .
Lossless compression of digital audio using cascaded RLS-LMS prediction
IEEE Trans. Speech and Audio Processing
IEEE Trans. Speech and Audio Processing
Computer Science