H. Sadjadpour, N. Sloane, M. Salehi, and G. Nebe, “Interleaver design for turbo codes”, IEEE Journal on Selected Area in Communications, Vol.19, No.5, 2001.
 J. Kaza and C. Chakrabarti, “Design and implementation of low-energy turbo decoders”, IEEE Transactions on Very Large Scale Integration Systems, Vol. 12. No. 9, 2004.
 K. Sun, D. Yuan, X. Zhou, “Performance analysis of turbo codes with different interleavers and decoding methods”, 2010 IEEE International Conference on Information Theory and Information Security, China
 Çatak E and Ata L, Adaptive filter bank-based multicarrier waveform design for flexible data rates. Computer and Electrical Engineering 2016; 6(2): 1-11.
 Ranjan R and Mitra D, HMM modeling for OFDM–BER performance. AEU - International Journal of Electronics and Communications 2015; 69(7): 18-25.
 Musbah S and Faouzi B, Comparison of OFDM and FBMC performance in multi-relay Conitive Radio Network. IEEE 978-1-4673-0762-8/12/, 2012; 756-760.
 Zeng Y, Liang, Chia M and Peh E, Unified Structure and parallel algorithm
The paper proposes the development of a wireless video camera that is used to capture images from any microscope, and is universally compatible with the standard C-Mount. The purpose behind developing this camera is to offer an economical alternative to the current high-priced microscopy camera without compromising performance. In addition this camera has the technology to work wirelessly.
presenting and analyzing bioimpedance data.
The advantage in machine learning methods is the possibility of learning generalizable predictive patterns in combining variables in a non-linear fashion, possibly increasing the predictive performance compared to simpler models. In addition, machine learning can be used to perform automatic feature extraction, useful when there is a lot of variables (e.g. different immittance parameters over many frequencies) and the important ones are not known. In some cases, such as clinical monitoring, the prediction performance is
Wireless Body Area Networks (WBANs) have been developed as the human-body monitoring systems to predict, diagnose, and treat diseases. Since the signal transmission in WBANs takes place in or around the human body the channel fading significantly affects packet error rate and overall network performance. This paper focuses on the design and demonstration of an ultra-wideband (UWB) modem to be used in the WBAN applications, and the evaluation of its performance over Rayleigh fading channel. Results show how the fading channel affects the performance of the system.
is implemented in open source reconstruction software EIDORS3.5 ( Polydorides and Lionheart 2002 ). It is verified on simulated data added with Gaussian noise. It is validated using the recently shared open EIT data (Hauptman et al . 2017) acquired from tank experiments. Further it is also validated using EIT data acquired for a papaya fruit using a system developed in our laboratory, with minimum 15 dB SNR. Results show that the DeTER technique improves quality of reconstructed images and reduces the background noise.
At the end, performance of DeTER is
Mohammad Karimi Moridani, Fatemeh Choopani and Mandana Kia
The purpose of this paper is to identify differences between abnormal and normal lung signals gathered by an EIT device, which is a new, non-invasive system that seeks the electrical conductivity and permittivity inside a body. Lung performances in patients are investigated using Phase Space Mapping technique on Electrical EIT signals. The database used in this paper contains 82 registered records of 52 individuals with proper lung volume. The results of this paper show that as the delay parameter (τ) increases, the SD1 parameter of phase space mapping indicates a significant difference between normal and abnormal lung volumes. The value of the SD1 parameter with τ = 6 in the case that the lung volume is in a normal condition is 342.57 ± 32.75 while it is 156.71 ± 26.01 in non-optimal mode. This method can be used to identify the patients’ lung volumes with chronic respiratory illnesses and is an accurate assessment of the diverse methods to treat respiratory system illnesses in addition to saving various therapeutic costs and dangerous consequences that are likely to occur by using improper treatment methods. It can also reduce the required treatment durations.
(PCA) feature reduction method in order to obtain ECG signal classification was applied in [ 14 ]. Some of the recently proposed works about the ECG signal analysis that utilized PCA for feature dimension reduction are given in [ 15 , 16 , 17 ]. The linear methods in ECG analyses provide good classification accuracy in free noise conditions but in the presence of noise, these linear techniques cannot acquire the maximum of accuracy [ 18 ]. So, using nonlinear methods better performance can be achieved under noisy conditions to exploit the hidden data from the ECG
Leslie D. Montgomery, Richard W. Montgomery, Wayne A. Gerth, Michael Bodo, Julian M. Stewart and Marty Loughry
(Army Institute of Surgical Research, San Antionio, Tx) equipped with an analogue-to-digital converter card (PCI 6052E, National Instruments, Austin, TX); both analogue-to-digital cards had 16 bit resolution. Data were processed off-line. BIS data were recorded by a laptop computer.
All animal protocols were submitted to, and approved by,appropriate Animal Use Committees prior to the performance of any animal testing. One animal was tested each day. Each test period lasted between 3-4 hours.
Results and Discussion
Results of Calf vs. Torso