The cortical, thalamic, and amygdaloid connections of the rodent temporal cortices were investigated by using anterograde transport iontophoretically injected biocytin. Injections into area Te1 labeled axons terminals in ventral regions dorsal subnuclei medial geniculate complex, Te3, rostrodorsal part Te2, ventrocaudal caudate putamen. No labeling was observed. Thalamic projections from Te2 targeted lateral posterior nucleus, subnucleus peripeduncular nucleus. Corticocortical mainly...

The differential efferent projections of the perirhinal cortex were traced by using anterograde and retrograde tracing techniques. dorsal bank (area 36) projected lightly to lateral entorhinal more strongly lateral, posterolateral cortical, posterior basomedial amygdaloid nuclei amygdalostriatal transition zone. ventral (dorsolateral cortex) cortex, subiculum, subfield CA1 mainly targeted basolateral nucleus. Corticocortical from banks different cortical areas. fundus rhinal sulcus 35) both...

Symbolic analysis has many applications in the design of analog circuits. Existing approaches rely on two forms symbolic-expression representation: expanded sum-of-product form and arbitrarily nested form. Expanded suffers problem that number product terms grows exponentially with size a circuit. Nested is neither canonical nor amenable to symbolic manipulation. In this paper, we present new approach exact by exploiting sparsity sharing terms. It consists representing determinant circuit...

In this article, we propose a sparse spectra graph convolutional network (SSGCNet) for epileptic electroencephalogram (EEG) signal classification. The goal is to develop lightweighted deep learning model while retaining high level of classification accuracy. To do so, weighted neighborhood field (WNFG) represent EEG signals. WNFG reduces redundant edges between nodes and has lower generation time memory usage than the baseline solution. sequential further developed from by combining weight...

Deep neural networks (DNNs) have proved their great potential over various perceptual and cognitive tasks with the cost of ever-growing storage capacity computation complexity. Sparse representations in emerged as a compelling method to achieve substantial reductions computational overhead energy consumption. However, introduction sparsity presents challenges such irregular memory accesses wasted cycles. Traditional methods attempted address these varied success, unfortunately, often...

This article presents a 13.56-MHz wireless power and data transfer receiver for implantable biomedical devices. To avoid the efficiency reduction of energy harvesting caused by large amplitude modulation (AM) depth (MD), maintain low-power consumption receiving, an envelope-detector-based with shifted limiters is designed signal demodulation. The detectable MD as low 0.1%. Moreover, dynamic impedance matching controller proposed to adjust input rectifier automatically thus optimize...

This paper presents an efficient algorithm for optimizing the area of power or ground networks in integrated circuits subject to reliability constraints. Instead solving original power/ground extracted from circuit layouts as previous methods did, new method first builds equivalent models many series resistors networks, then sequence linear programming [9] is used solve simplified networks. The solutions are back solved optimized, simply exploits regularities Experimental results show that...

An energy-efficient charge pump (CP) for solar energy harvesting is presented. A multistep split–merge transfer operation introduced to replace the traditional one-step process. Theoretically, this method increases amount of transferred by up 26% while reducing Joule heat power loss 7%. five-stage complementary CP was designed and fabricated in a 0.13- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math...

A graph-based approach is presented for the generation of exact symbolic network functions in form rational polynomials complex frequency variable s analog integrated circuits. The employs determinant decision diagrams (DDDs) to represent a circuit matrix and its cofactors. notion multiroot DDDs introduced, where each root represents expression an individual coefficient powers numerator denominator function, multiple roots share their common subgraphs. DDD-based algorithm generating...

A new method is proposed for hierarchical symbolic analysis of large analog integrated circuits. It consists performing suppression each subcircuit to its terminals in terms matrix determinants and cofactors, applying Cramer's rule symbolically solve the set equations at top level circuit hierarchy. An annotated, directed, acyclic graph, called determinant decision diagram (DDD), used represent matrices cofactors suppression, as well top-level required rule. DDD enables us systematically...

This paper presents a new method for determining the widths of power and ground routes in integrated circuits so that area required by is minimized subject to reliability constraints. The basic idea transform resulting constrained nonlinear programming problem into sequence linear programs. Theoretically, we show programs always converges optimum solution relaxed convex problem. Experimental results demonstrate sequence-of-linear-programming orders magnitude faster than best-known based on...

In this paper, a new formulation for coupled circuit-electromagnetic (EM) simulation is presented. The employs full-wave integral equations to model the EM behavior of two- or three-dimensional structures while using modified nodal analysis circuit interactions. A coupling scheme based on charge and current continuity potential matching, realized as generalization Kirchoff's voltage laws, ensures that interactions can be formulated seamless system. While rigorous port models obtained...

This paper presents a new method of sizing the widths power and ground routes in integrated circuits so that chip area required by is minimized subject to electromigration IR voltage drop constraints. The basic idea transform underlying constrained nonlinear programming problem into sequence linear programs. Theoretically, we show (that programs always converges optimum solution relaxed convex optimization problem. Experimental results demonstrate proposed sequence-of-linear-program Is...

Layout parasitics can significantly affect the performance of analog integrated circuits (ICs). In this paper, a systematic method optimizing an existing layout considering is presented for technology migration and retargeting. This represents locations rectangle edges as variables extracts circuit integrity such device symmetry, matching, design rules constraints. To ensure desired performance, bounds are determined first. These used to constrain geometries while retargeting high-quality...

The strong impact of layout intricacies on analog-circuit performance poses great challenges to analog automation. Recently, template-based methods have been shown be effective in reuse-centric automation for CMOS blocks such as operational amplifiers. layout-retargeting method first creates a template by extracting set constraints from an existing representation. From this template, new layouts are then generated corresponding technology processes and device specifications. For large...

A new graph reduction approach to symbolic circuit analysis is developed in this paper. Binary Decision Diagram (BDD) mechanism formulated, together with a specially designed process and recursive sign determination algorithm. analog simulator using combination of these techniques. The able analyze large circuits the frequency domain. Experimental results are reported.

Implantable and wearable devices require both wireless power transfer (WPT) data transmission (WDT) in biomedical systems [1-3], e.g., neural recording applications [4]. Very often, amplitude modulation (AM) is preferred these due to its lower consumption less circuit complexity (de)modulation. To achieve the required bit-error rate (BER) than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> , a large depth (MD), typically range of 8%...

This paper presents OCEAN: an artificial neural network processor designed for accelerating gated-recurrent-unit (GRU) inference and on-chip incremental learning sequential modeling. Implemented in 65-nm CMOS with silicon area of 2.9 × 3.5 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the OCEAN features a 32-bit reduced instruction set computing core, 64-KB SRAM, eight 16-bit four-cell GRU accelerators gradient computation. Each...

This paper presents an 8-channel energy-efficient analog front-end (AFE) for neural recording, with improvements in power supply rejection ratio (PSRR) and dynamic range. The input stage the low noise amplifier (LNA) adopts voltage (0.35 V) current-reusing to achieve ultralow power. To maintain a high PSRR performance while using such low-voltage supply, replica-biasing scheme is proposed generate stable bias current of LNA despite large interference. By exploiting signal characteristics...