FAILURE TOLERANT SYNCHRONOUS AND SELT-TIED CIRCUITS COMPARISON

The article considers the problem of developing synchronous and self-timed (ST) digital circuits that are tolerant to soft errors. Synchronous circuits traditionally use the 2-of-3 voting principle to ensure single failure, resulting in three times the hardware costs. In ST circuits, due to dual-rail signal coding and two-phase control, even duplication provides a soft error tolerance level 2.1 to 3.5 times higher than the triple modular redundant synchronous counterpart. The development of new high-precision software simulating microelectronic failure mechanisms will provide more accurate estimates for the electronic circuits' failure tolerance

Coding and robustness of signal processing in streaming recurrent neural networks

Introduction: When substantiating promising architectures of streaming recurrent neural networks, it becomes necessary to assess their stability in processing various input signals. For this, stability diagrams are constructed containing the results of simulation for each of the nodes of these diagrams. Such an estimation can be time-consuming and computationally intensive, especially when analyzing large neural networks. Purpose: Search for methods of quick construction of such diagrams and assessing the stability of streaming recurrent neural networks. Results: Analysis of the features of the stability diagrams under study showed that the nodes of the diagrams are grouped into continuous zones with the same ratio characteristics of the input signal processing defects. With this in mind, the article proposes a method for constructing these diagrams based on bypassing the boundaries of their zones. With this approach, you do not have to perform simulation for the interior nodes of each zone. The simulation should be performed only for the nodes adjacent to zone boundaries. Due to this, the number of nodes for which you need to perform simulation sessions is reduced by an order of magnitude. The influence of the input signal coding types on the streaming recurrent neural network stability has been investigated. It is shown that the representation of input signals in the form of sequences of single pulses with intersecting elements can provide greater stability as compared to pulses without any intersection.

Dictionaries and algorithms for sparsity constrained image reconstruction

There has been a growing interest in the different types of dictionaries that can be used in image processing applications. We propose a hybrid dictionary composed of transform based atoms and additional nonlinear atoms generated using the polynomial, rectangular and exponential functions. The additional nonlinear atoms improve signal reconstruction quality for both transient and smooth signals. To further improve signal reconstruction quality, we optimize the hybrid dictionary using training samples from the signal. We also propose a signal coding algorithm that generates additional atoms by performing a circular shift on the provided dictionary prior to coding the signal. We have evaluated the proposed methods against existing predefined dictionaries by visually examining the reconstructed images as well as evaluating the peak signal to noise ratio of the reconstructed signal. All methods proposed in this thesis improved signal reconstruction quality however; we require an in-depth cost analysis study to evaluate its limitations.

Dictionaries and algorithms for sparsity constrained image reconstruction

There has been a growing interest in the different types of dictionaries that can be used in image processing applications. We propose a hybrid dictionary composed of transform based atoms and additional nonlinear atoms generated using the polynomial, rectangular and exponential functions. The additional nonlinear atoms improve signal reconstruction quality for both transient and smooth signals. To further improve signal reconstruction quality, we optimize the hybrid dictionary using training samples from the signal. We also propose a signal coding algorithm that generates additional atoms by performing a circular shift on the provided dictionary prior to coding the signal. We have evaluated the proposed methods against existing predefined dictionaries by visually examining the reconstructed images as well as evaluating the peak signal to noise ratio of the reconstructed signal. All methods proposed in this thesis improved signal reconstruction quality however; we require an in-depth cost analysis study to evaluate its limitations.

The influence of rhythm on short-term memory for serial order

In the field of verbal short-term memory (STM), numerous theoretical models have been proposed to explain how serial order information is processed and represented. Evidence suggests that serial order is represented through associations between items and a varying contextual signal coding the position of each item in a sequence, but the nature of this contextual signal is still a matter of debate (i.e., event-based vs. time-based varying signal). According to event-based models of serial order, the contextual signal coding serial order is not sensitive to temporal manipulations, as it is the case in irregularly timed sequences. Up to now, the study of the temporal factors influencing serial order STM has been limited to temporal grouping and temporal isolation effects. The goal of the present study is to specify in more detail the role played by temporal factors in serial order STM tasks. To accomplish this, we compared recall performance and error patterns for sequences presenting items at a regular or an irregular and unpredictable timing in three experiments. The results showed that irregular timing does not affect serial recall nor the pattern of errors. These data clearly favour the view that serial order in verbal STM is represented with event-based rather than time-based codes.

MIMO radar signals with better correlation characteristics

MIMO radars employ multiple transmitting and receiving antennae. For each transmitting antenna, an independent and easily distinguishable signal is required, and appropriate filters must be used by the receiver. For this, the transmitted signals should have characteristics, enabling their effective separation. In this paper the correlation characteristics of selected signals are compared, and the appropriate signal coding is suggested. For differentiation, we address signals with basic linear or nonlinear frequency modulation (LFM or NLFM) multiplied by Gold, PRN, or frequency diversity (FD) codes. The analysis shows that better signal characteristics are achieved using the FD than the other codes. Using matched filters with filter length of 511, sidelobes and cross-correlations are suppressed by 40 dB with FD codes, while with the other codes only 20 dB was achieved. It was also proven, that the FD codes are more tolerant to the Doppler shift. On the other hand, the FD codes application leads to an extension of the overall transmitted signal bandwidth. This however, only represents a serious barrier for very broadband radar systems.

The Impact of Optogenetics on Regenerative Medicine

Optogenetics is a novel strategic field that combines light (opto-) and genetics (genetic) into applications able to control the activity of excitable cells and neuronal circuits. Using genetic manipulation, optogenetics may induce the coding of photosensitive ion channels on specific neurons: this non-invasive technology combines several approaches that allow users to achieve improved optical control and higher resolution. This technology can be applied to optical systems already present in the clinical-diagnostic field, and it has also excellent effects on biological investigations and on therapeutic strategies. Recently, several biomedical applications of optogenetics have been investigated, such as applications in ophthalmology, in bone repairing, in heart failure recovery, in post-stroke recovery, in tissue engineering, and regenerative medicine (TERM). Nevertheless, the most promising and developed applications of optogenetics are related to dynamic signal coding in cell physiology and neurological diseases. In this review, we will describe the state of the art and future insights on the impact of optogenetics on regenerative medicine.