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This paper proposes a nonlinear adaptive decoder for somatosensory micro-stimulation based on the kernel least mean square (KLMS) algorithm applied directly on the space of spike trains. Instead of using a binned representation of spike trains, we transform the vector of spike times into a function in reproducing kernel Hilbert space (RKHS), where the inner product of two spike time vectors is defined...
This paper presents the design and functional simulation of a new multi-level bang-bang phase detector for use in a clock and data recovery circuit (CDR). The designed phase detector provides information of the nature of the delay between its input signals in a digitised manner, establishing six levels of quantisation. To avoid the metastability that hinders the performance of traditional bang-bang...
This paper presents a new CMOS analog equalizer for short-reach optical communications. The circuit has been designed in a standard 0.18 µm CMOS process. The equalizer is aimed for multi-gigabit short-range applications, targeting up to 3.125 Gbps through a 50 m SI-POF. The proposed structure operates with a supply voltage of 1 V and has a power consumption of 2.5 mW.
This paper introduces a kernel adaptive filter implemented with stochastic gradient on temporal differences, kernel Temporal Difference (TD)(λ), to estimate the state-action value function in reinforcement learning. The case λ=0 will be studied in this paper. Experimental results show the method's applicability for learning motor state decoding during a center-out reaching task performed by a monkey...
In this work, we develop an experimental testbed that couples biotic and abiotic metrics for studying, quantifying and predicting the effects of chronic electrode implantation on neural electrode performance. The rationale is based on the observation that long-term functionality is the outcome of the interactions between the dynamics of the neuronal environment and the properties of the electrode...
To automatically synthesize multi-scroll chaotic attractors, fundamental trade-offs on the nonlinear function must be analyzed and exploited. This paper proposes to use a surrogate function to approximate the trade-off between the operating frequency and the behavior of the switching points of the nonlinear function, which is a saturated nonlinear function series approximated by a piece-wise linear...
In this paper, a chaotic synchronization scheme for multi-directional multi-scroll chaos generators is presented. We use Generalized Hamiltonian forms approach to determine the synchronization conditions for two unidirectionally coupled multi-directional multi-scroll chaotic attractors. First, two state-variables of the master system are used to control the two nonlinear functions in the slave system...
Since multi-scroll chaotic oscillators are known to have many challenges due to the parasitic effects in the circuit implementation, this paper analyzes their effect on the non-ideal slopes and presence of delays in the realization of the saw-tooth nonlinear function which is used to generate these oscillators. The proposed analysis and description is applicable for any comparator-based nonlinear...
The use of tunable matching networks (TMNs) for antenna tuning and efficiency enhancement is well-known. However, finding the optimum TMN state or configuration is not an easy task. If we are able to estimate the load impedance, the TMN state choice can be done quickly and properly. In this paper we propose a new technique to estimate a complex load impedance with scalar measurements at three different...
Microstrip to parallel-strip transitions are frequently used for feeding balanced antenna structures, such as dipoles and printed spiral antennas. In this paper, we propose an analytical method to compute the gradual taper using a Hecken approach to minimize the return losses. The proposed method is verified experimentally with the aid of three transitions including matching capabilities with different...
In this paper, a 3.125 GHz four stage voltage controlled ring oscillator is presented. The oscillator has been designed in a 0.18 µm CMOS process with a 1.8 V supply. Behavioural simulations predict an 18% tuning range for the oscillator, with a −91 dBc/Hz phase noise at a 1 MHz offset. Its power consumption has been simulated to be only 12.6 mW.
A trade-off analysis on the number of scrolls and the operating frequency is presented. To do so, nonlinear system parameters, real physical active device parameters and the operating frequency are taken into account to model the behavior of the saturated nonlinear function series approximated by a piecewise-linear description. As a consequence, not only the trade-off between the number of scrolls...
Currently the market and the academic community have required applications of image and video processing with several real-time constraints. In order to seek an alternative design that allows the rapid development of real time image processing systems this paper proposes an unified hardware architecture for some image filtering algorithms in space domain, such as windowing-based operations, which...
In this work, we design and test a framework for neural decoding in Brain-Machine Interfaces based on the Perception Action Reward Cycle (PARC). Here the neural decoder in the BMI learns to translate motor neural states in the primary motor cortex (M1) into actions based on a reward signal estimated directly from Neucleus Accumbens (NAcc). The control architecture was designed based on the Actor-Critic...
Experiments for the online closed-loop control of neural prosthetics require feedback within 100ms. In a typical neurophysiology laboratory with local computing machines, a majority of this time is spent on acquiring and analyzing the neural signals and a minority (i.e. less than a millisecond) is actual data transfer among machines on local- or campus-area networks. However, the local computing machines...
In this work, we develop an experimental primate test bed for a center-out reaching task to test the performance of reinforcement learning based decoders for Brain-Machine Interfaces. Neural recordings obtained from the primary motor cortex were used to adapt a decoder using only sequences of neuronal activation and reinforced interaction with the environment. From a naïve state, the system was able...
Precise control of neural circuits via microstimulation is an indispensable but challenging objective in neuro-engineering. The effect of electrical stimulation is imprecise and has a spatio-temporal blurring. At the neuron level, the effects are obfuscated by the complexity of neural dynamics. This paper proposes an online multiple-input-multiple-output (MIMO) adaptive inverse controller for somatosensory...
Visualizing the collective modulation of multiple neurons during a known behavioral task is useful for exploratory analysis, but handling the large dimensionality of neural recordings is challenging. We further investigate using static dimensionality reduction techniques on neural firing rate data during an arm movement task. This lower-dimensional representation of the data is able to capture the...
Current drugs used to treat atrial fibrillation (AF) often target tissue excitability (sodium channels) and refractoriness (hERG channels), but their efficacy is still modest. This study focuses on investigating new approaches to manage AF by conducting a systematic computer simulation study. The Maleckar action potential (AP) model was used to simulate human atrial cellular and tissue electrophysiology...
This article proposes a biometric technique based on gesture recognition performed directly in a mobile device embedding an accelerometer. As time consumption is an essential requirement, this article aims to discover the most distinctive acceleration axis information in order to find the best strategy considering EER and consumed time. Best EER result of 2.5% has been obtained when the information...
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