Visible to the public Biblio

Filters: Keyword is IIR filters  [Clear All Filters]
2020-08-03
Saxena, Shubhankar, Jais, Rohan, Hota, Malaya Kumar.  2019.  Removal of Powerline Interference from ECG Signal using FIR, IIR, DWT and NLMS Adaptive Filter. 2019 International Conference on Communication and Signal Processing (ICCSP). :0012–0016.
ECG signals are often corrupted by 50 Hz noise, the frequency from the power supply. So it becomes quite necessary to remove Power Line Interference (PLI) from the ECG signal. The reference ECG signal data was taken from the MIT-BIH database. Different filtering techniques comprising of Discrete Wavelet Transform (DWT), Normalized Least Mean Square (NLMS) filter, Finite Impulse Response (FIR) filter and Infinite Impulse Response (IIR) filter were used in this paper for denoising the ECG signal which was corrupted by the PLI. Later, the comparison was made among the methods, to find the best methodology to denoise the corrupted ECG signal. The parameters that were used for the comparison are Mean Square Error (MSE), Mean Absolute Error (MAE), Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR). Higher values of SNR & PSNR and lower values of MSE & MAE define the best denoising algorithm.
2020-02-26
Qiu, Tongsheng, Wang, Xianyi, Tian, Yusen, Du, Qifei, Sun, Yueqiang.  2019.  A System Design of Real-Time Narrowband Rfi Detection And Mitigation for Gnss-R Receiver. IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. :5167–5170.

With the rapid development of radio detection and wireless communication, narrowband radio-frequency interference (NB-RFI) is a serious threat for GNSS-R (global navigation satellite systems - reflectometry) receivers. However, interferometric GNSS-R (iGNSS-R) is more prone to the NB-RFIs than conventional GNSS-R (cGNSS-R), due to wider bandwidth and unclean replica. Therefore, there is strong demand of detecting and mitigating NB-RFIs for GNSS-R receivers, especially iGNSS-R receivers. Hence, focusing on working with high sampling rate and simplifying the fixed-point implementation on FPGA, this paper proposes a system design exploiting cascading IIR band-stop filters (BSFs) to suppress NB-RFIs. Furthermore, IIR BSF compared with IIR notch filter (NF) and IIR band-pass filter (BPF) is the merely choice that is able to mitigate both white narrowband interference (WNBI) and continuous wave interference (CWI) well. Finally, validation and evaluation are conducted, and then it is indicated that the system design can detect NB-RFIs and suppress WNBI and CWI effectively, which improves the signal-to-noise ratio (SNR) of the Delay-Doppler map (DDM).

2017-12-27
Pich, R., Chivapreecha, S., Prabnasak, J..  2017.  A new key generator for data encryption using chaos in digital filter. 2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC). :87–92.

The presented work of this paper is to propose the implementation of chaotic crypto-system with the new key generator using chaos in digital filter for data encryption and decryption. The chaos in digital filter of the second order system is produced by the coefficients which are initialed in the key generator to produce other new coefficients. Private key system using the initial coefficients value condition and dynamic input as password of 16 characters is to generate the coefficients for crypto-system. In addition, we have tension specifically to propose the solution of data security in lightweight cryptography based on external and internal key in which conducts with the appropriate key sensitivity plus high performance. The chaos in digital filter has functioned as the main major in the system. The experimental results illustrate that the proposed data encryption with new key generator system is the high sensitive system with accuracy key test 99% and can make data more secure with high performance.

2015-05-06
Tuia, D., Munoz-Mari, J., Rojo-Alvarez, J.L., Martinez-Ramon, M., Camps-Valls, G..  2014.  Explicit Recursive and Adaptive Filtering in Reproducing Kernel Hilbert Spaces. Neural Networks and Learning Systems, IEEE Transactions on. 25:1413-1419.

This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the γ-filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time series prediction, complex nonlinear system identification, and adaptive antenna array processing demonstrate the potential of the approach for scenarios where recursivity and nonlinearity have to be readily combined.