Vector quantization and signal compression
Vector quantization and signal compression
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Proceedings of the 3rd international symposium on Information processing in sensor networks
Recursive filtering with non-Gaussian noises
IEEE Transactions on Signal Processing
Hidden Markov model-based packet loss concealment for voice over IP
IEEE Transactions on Audio, Speech, and Language Processing
On the DPCM compression of Gaussian autoregressive sequences
IEEE Transactions on Information Theory
Packet Video Error Concealment With Gaussian Mixture Models
IEEE Transactions on Image Processing
Hi-index | 35.70 |
We present a new design method for robust low-delay coding of autoregressive (AR) sources for transmission across erasure channels. It is a fundamental rethinking of existing concepts. It considers the encoder a mechanism that produces signal measurements from which the decoder estimates the original signal. The method is based on linear predictive coding and Kalman estimation at the decoder. We employ a novel encoder state-space representation with a linear quantization noise model. The encoder is represented by the Kalman measurement at the decoder. The presented method designs the encoder and decoder offline through an iterative algorithm based on closed-form minimization of the trace of the decoder state error covariance. The design method is shown to provide considerable performance gains, when the transmitted quantized prediction errors are subject to loss, in terms of signal-to-noise ratio (SNR) compared to the same coding framework optimized for no loss. The design method applies to stationary auto-regressive sources of any order. We demonstrate the method in a framework based on a generalized differential pulse code modulation (DPCM) encoder. The presented principles can be applied to more complicated coding systems that incorporate predictive coding as well.