Digital Filters: Analysis, Design and Applications

By A. Antoniou. 2018

535 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/918d963d81bb5081d920db3367311cf63eb735b5

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1. Seyedali Mirjalili
2. Esmat Rashedi
3. Hossein Nezamabadi-pour
4. Saeid Saryazdi
5. Abbes Amira
6. Pramod Kumar Meher
7. S. Chandrasekaran
8. Zahra Beheshti

Citations in the corpus

• Filter modeling using gravitational search algorithm (2011, background): “Linear digital filters can be classified into two groups based on their structures: infinite impulse response (IIR) and finite impulse response (FIR; Oppenheim et al., 1999; Mitra and Kaiser, 1993; Antoniou, 1993).”
• FPGA Realization of FIR Filters by Efficient and Flexible Systolization Using Distributed Arithmetic (2008, background): “F INITE-IMPULSE-RESPONSE (FIR) digital filters are extensively used due to their key role in various digital signal processing (DSP) applications [1], [2].”
• The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference. (2014, unknown): “We have previously shown that multivariate G-causality, conditional and unconditional and in both time and frequency domains, is theoretically invariant under the application of (almost) arbitrary stable, invertible 15 digital filters (Antoniou, 1993; Barnett and Seth, 2011).”