Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Audio Signal Processing for Next-Generation Multimedia Communication Systems
Audio Signal Processing for Next-Generation Multimedia Communication Systems
The quaternion LMS algorithm for adaptive filtering of hypercomplex processes
IEEE Transactions on Signal Processing
Maxflat fractional delay IIR filter design
IEEE Transactions on Signal Processing
Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
Quaternion-MUSIC for vector-sensor array processing
IEEE Transactions on Signal Processing
Complex random vectors and ICA models: identifiability, uniqueness, and separability
IEEE Transactions on Information Theory
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A learning algorithm for the training of quaternion valued adaptive infinite impulse (IIR) filters is introduced. This is achieved by taking into account specific properties of stochastic gradient approximation in the quaternion domain and the recursive nature of the sensitivities within the IIR filter updates, to give the quaternion-valued stochastic gradient algorithm for adaptive IIR filtering (QSG-IIR). Further, to reduce computational complexity, a variant of the QSG-IIR is introduced, which for small stepsizes makes better use of the available information. Stability analysis and simulations on both synthetic and real world 4D data support the approach.