Abstract: The present disclosure illustrates an acoustic echo cancellation method and system using the same. The acoustic echo cancellation method comprises the following steps. Firstly, a prior-knowledge matrix comprising a plurality of space vectors is built. Then, an initial filter vector is generated by the prior-knowledge matrix and an initial weighting vector. The weighting vector is updated based on the difference of the echo signal and the estimated signal in an iteration algorithm, and the coefficient of the filter vector is updated according to the updated weighting vector. An estimated signal is generated according to the updated filter vector and the original signal. Finally, the next echo signal is cancelled by the near-end estimated signal.

Abstract: The present disclosure illustrates an acoustic echo cancellation method and system using the same. The acoustic echo cancellation method comprises the following steps. Firstly, a prior-knowledge matrix comprising a plurality of space vectors is built. Then, an initial filter vector is generated by the prior-knowledge matrix and an initial weighting vector. The weighting vector is updated based on the difference of the echo signal and the estimated signal in an iteration algorithm, and the coefficient of the filter vector is updated according to the updated weighting vector. An estimated signal is generated according to the updated filter vector and the original signal. Finally, the next echo signal is cancelled by the near-end estimated signal.

Abstract: An indoor positioning system comprises at least one signal source disposed in an indoor environment having training points, and storage and positioning devices coupled with each other. The signal source has power levels, based on one of which it transmits a wireless signal. The storage device stores for each training point a first signal strength, and for at least one adaptation point among the training points a second signal strength. The first and second signal strengths are associated respectively with a first and a second power level among the power levels. The positioning device obtains a current signal strength observed at a current location and its associated current power level, calculates a third signal strength for each training point based on the first, second and current power levels and the first and second signal strengths, and compares the current and third signal strengths to estimate the current location.