Time series forecasting provides a vital basis for the control and management of various systems. The time data in real world are usually strongly nonstationary nonlinear, which increases difficulty reliable forecasting. To fully utilize learning capability machine forecasting, an adaptive broad echo state network (ABESN) is proposed this paper. Firstly, system (BLS) used as framework, reservoi...

Acoustic echoes arise whenever there is acoustic coupling between a loudspeaker and a microphone. A traditional solution for eliminating the undesired echo signal is an acoustic echo canceler (AEC), which identifies the echo path between a loudspeaker and a microphone by means of an adaptive filter. The echo signal can be canceled successfully when the modeling filter approaches the true echo p...

SODAR stands for SOund Detection And Ranging. A SODAR uses sound pulses at a frequency of about 2kHz to detect turbulence and measure wind speeds. Turbulence in the atmosphere reflects a portion of the acoustic energy back towards the ground. The SODAR measures the strength, time delay and doppler shift of these echoes. The time delay of the echo determines the height from which the echo return...

This paper presents a new assessment of four approaches to acoustic echo cancellation in the presence of non-linear echo. The comparison is performed with algorithms that are configured to give equivalent performance under linear-only echo conditions, thereby giving a more meaningful assessment. We also compare the effect of non-linear echo to that of noise and show that, whilst performance dif...

An overview is given on the fundamental problems when combining acoustic echo cancellation (AEC) with adaptive beamforming microphone array (ABMA) in fullduplex communications. For reasons of computational complexity and functionality, a compromise is necessary between one echo canceller per microphone signal and a single echo canceller for the beamforming output. Here, the decomposition of the...