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.

Non-Invasive Human Brain 
Stimulation in Cognitive Neuroscience: A Primer

The use of non-invasive brain stimulation is widespread in studies of human cognitive neuroscience. This has led to some genuine advances in understanding perception and cognition, and has raised some hopes of applying the knowledge in clinical contexts. There are now several forms of stimulation, the ability to combine these with other methods, and ethical questions that are special to brain stimulation. In this Primer, we aim to give the users of these methods a starting point and perspective from which to view the key questions and usefulness of the different forms of non-invasive brain stimulation. We have done so by taking a critical view of recent highlights in the literature, selected case studies to illustrate the elements necessary and sufficient for good experiments, and pointed to questions and findings that can only be addressed using interference methods