A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECG data compression by spline approximation
Signal Processing
A genetic-designed beta basis function neural network for multi-variable functions approximation
Systems Analysis Modelling Simulation - Special issue: Advances in control and computer engineering
ECG compression method using Lorentzian functions model
Digital Signal Processing
ECG signal compression by multi-iteration EZW coding for different wavelets and thresholds
Computers in Biology and Medicine
A novel algorithm for wavelet based ECG signal coding
Computers and Electrical Engineering
Constrained ECG compression algorithm using the block-based discrete cosine transform
Digital Signal Processing
Embedded filter bank-based algorithm for ECG compression
Signal Processing
A 2-D ECG compression algorithm based on wavelet transform and vector quantization
Digital Signal Processing
A linear quality control design for high efficient wavelet-based ECG data compression
Computer Methods and Programs in Biomedicine
Beta wavelets. Synthesis and application to lossy image compression
Advances in Engineering Software - Advanced algorithms and architectures for signal processing
Computers and Electrical Engineering
Wavelet-based low-delay ECG compression algorithm for continuous ECG transmission
IEEE Transactions on Information Technology in Biomedicine
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In this paper, a wavelet based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs new wavelet filters whose coefficients are derived with beta function and its derivatives. A comparative study of performance of different existing wavelet filters and the Beta wavelet filters is made in terms of compression ratio (CR), percent root mean square difference (PRD), mean square error (MSE) and signal-to-noise ratio (SNR). When compared, the Beta wavelet filters give better compression ratio and also yields good fidelity parameters as compared to other wavelet filters. The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.