Removal of multiple artifacts from ECG signal using cascaded multistage adaptive noise cancellers

Although cascaded multistage adaptive noise cancellers have been employed before by researchers for multiple artifact removal from the ElectroCardioGram (ECG) signal, they all used the same adaptive algorithm in all the cascaded multi-stages for adjusting the adaptive filter weights. In this paper, we propose a cascaded 4-stage adaptive noise canceller for the removal of four artifacts present in the ECG signal, viz. baseline wander, motion artifacts, muscle artifacts, and 60 Hz Power Line Interference (PLI). We have investigated the performance of eight adaptive algorithms, viz. Least Mean Square (LMS), Least Mean Fourth (LMF), Least Mean Mixed-Norm (LMMN), Sign Regressor Least Mean Square (SRLMS), Sign Error Least Mean Square (SELMS), Sign-Sign Least Mean Square (SSLMS), Sign Regressor Least Mean Fourth (SRLMF), and Sign Regressor Least Mean Mixed-Norm (SRLMMN) in terms of Signal-to-Noise Ratio (SNR) improvement for removing the aforementioned four artifacts from the ECG signal. We employed the LMMN, LMF, LMMN, LMF algorithms in the proposed cascaded 4-stage adaptive noise canceller to remove the respective ECG artifacts as mentioned above. We succeeded in achieving an SNR improvement of 12.7319 dBs. The proposed cascaded 4-stage adaptive noise canceller employing the LMMN, LMF, LMMN, LMF algorithms outperforms those that employ the same algorithm in the four stages. One unique and powerful feature of our proposed cascaded 4-stage adaptive noise canceller is that it employs only those adaptive algorithms in the four stages, which are shown to be effective in removing the respective ECG artifacts as mentioned above. Such a scheme has not been investigated before in the literature

Towards High Fidelity Quantum Computation and Simulation with Rydberg Atoms

Individually trapped neutral atoms are a promising candidate for use in quantum computing and simulation applications. They are highly scalable, have long coherence times and can be entangled via strong dipole-dipole interactions by driving to highly excited Rydberg states. However, the fidelity of single atom operations as well as two-atom entangling operations is limited by intrinsic sources of decoherence such as atomic motion, as well as technical sources of noise such as laser intensity fluctuations and phase/frequency fluctuations. We study the effect of these factors on single atom Rabi oscillations and two-atom Rydberg blockaded Rabi oscillations, using perturbation theory and numerical simulation. We develop a window function approach which helps us qualitatively understand the significance of the different spectral components of the noise as well as quantitatively understand the dependence of the Rabi oscillation fidelity on Rabi frequency. This allows us to predict the maximum experimentally achievable fidelities using independent measurements of experimental parameters such as noise spectra and atomic temperature. Turning to the question of near-term scalability of the experimental system, we prototype and test a method of generating a ’ladder’ configuration of optical tweezers utilizing two independent lasers. Our setup allows us to fully tune the geometry of the ladder, namely the separation between the two rows, the angle between them, and their relative position along the axis of the ladder. This pseudo-2D configuration enables us to reach larger system sizes in the near future and allows us to access beyond 1D physics

Increasing the speed of parallel decoding of turbo codes

Turbo codes experience a significant decoding delay because of the iterative nature of the decoding algorithms, the high number of metric computations and the complexity added by the (de)interleaver. The extrinsic information is exchanged sequentially between two Soft-Input Soft-Output (SISO) decoders. Instead of this sequential process, a received frame can be divided into smaller windows to be processed in parallel. In this paper, a novel parallel processing methodology is proposed based on the previous parallel decoding techniques. A novel Contention-Free (CF) interleaver is proposed as part of the decoding architecture which allows using extrinsic Log-Likelihood Ratios (LLRs) immediately as a-priori LLRs to start the second half of the iterative turbo decoding. The simulation case studies performed in this paper show that our parallel decoding method can provide %80 time saving compared to the standard decoding and %30 time saving compared to the previous parallel decoding methods at the expense of 0.3 dB Bit Error Rate (BER) performance degradation

A comparative study on the modified Max-Log-MAP turbodecoding by extrinsic information scaling

A simple but effective technique to improve the performance of the Max-Log-MAP algorithm is to scale the extrinsic information exchanged between two MAP decoders. A comprehensive analysis of the selection of the scaling factors according to channel conditions and decoding iterations is presented in this paper. Choosing a constant scaling factor for all SNRs and iterations is compared with the best scaling factor selection for changing channel conditions and decoding iterations. It is observed that a constant scaling factor for all channel conditions and decoding iterations is the best solution and provides a 0.2-0.4 dB gain over the standard Max- Log-MAP algorithm. Therefore, a constant scaling factor should be chosen for the best compromise

The modified Max-Log-MAP turbo decoding algorithm by extrinsic information scaling for wireless applications

The iterative nature of turbo-decoding algorithms increases their complexity compare to conventional FEC decoding algorithms. Two iterative decoding algorithms, Soft-Output-Viterbi Algorithm (SOVA) and Maximum A posteriori Probability (MAP) Algorithm require complex decoding operations over several iteration cycles. So, for real-time implementation of turbo codes, reducing the decoder complexity while preserving bit-error-rate (BER) performance is an important design consideration. In this chapter, a modification to the Max-Log-MAP algorithm is presented. This modification is to scale the extrinsic information exchange between the constituent decoders. The remainder of this chapter is organized as follows: An overview of the turbo encoding and decoding processes, the MAP algorithm and its simplified versions the Log-MAP and Max-Log-MAP algorithms are presented in section 1. The extrinsic information scaling is introduced, simulation results are presented, and the performance of different methods to choose the best scaling factor is discussed in Section 2. Section 3 discusses trends and applications of turbo coding from the perspective of wireless applications

Analysis of Next-generation Sequencing Data in Virology - Opportunities and Challenges

Viruses are the most abundant and the smallest organisms, which are relatively simple to sequence. Genome sequence data of viruses for individual species to populations outnumber that of other species. Although this offers an opportunity to study viral diversity at varying levels of taxonomic hierarchy, it also poses challenges for systematic and structured organization of data and its downstream processing. Extensive computational analyses using a number of algorithms and programs have opened exciting opportunities for virus discovery and diagnostics, apart from augmenting our understanding of the intriguing world of viruses. Unravelling evolutionary dynamics of viruses permits improved understanding of phenomena such as quasispecies diversity, role of mutations in host switching and drug resistance, which enables the tangible measurements of genotype and phenotype of viruses. Improved understanding of geno-/serotype diversity in correlation with antigenic diversity will facilitate rational design and development of efficacious vaccines against emerging and re-emerging viruses. Mathematical models developed using the genomic data could be used to predict the spread of viruses due to vector switching and the (re)emergence due to host switching and, thereby, contribute towards designing public health policies for disease management and control

Stability analysis of higher-order delta-sigma modulators for sinusoidal inputs

The aim of this paper is to determine the stability of higher-order Δ-Σ modulators for sinusoidal inputs. The nonlinear gains for the single bit quantizer for a dual sinusoidal input have been derived and the maximum stable input limits for a fifth-order Chebyshev Type II based Δ-Σ modulators are established. These results are useful for optimising the design of higher-order Δ-Σ modulators

Parallel decoding of turbo codes using multi-point trellis termination and collision-free interleavers

The UMTS turbo encoder is composed of parallel concatenation of two Recursive Systematic Convolutional (RSC) encoders which start and end at a known state. This trellis termination directly affects the performance of turbo codes. This paper presents performance analysis of multi-point trellis termination of turbo codes which is to terminate RSC encoders at more than one point of the current frame while keeping the interleaver length the same. For long interleaver lengths, this approach provides dividing a data frame into sub-frames which can be treated as independent blocks. A novel decoding architecture using multi-point trellis termination and collision-free interleavers is presented. Collision-free interleavers are used to solve memory collision problems encountered by parallel decoding of turbo codes. The proposed parallel decoding architecture reduces the decoding delay caused by the iterative nature and forward-backward metric computations of turbo decoding algorithms. Our simulations verified that this turbo encoding and decoding scheme shows Bit Error Rate (BER) performance very close to that of the UMTS turbo coding while providing almost %50 time saving for the 2-point termination and %80 time saving for the 5-point termination