Sequence Tagging, including part of speech tagging, chunking and named entity recognition, is an important task in NLP. Recurrent neural network models such as Bidirectional LSTMs have produced impressive results on sequence tagging. In this work, we first present a Bidirectional LSTM neural network model for sequence tagging tasks. Then we show a simple and fast greedy sequence tagging system ...

This paper proposes a new architecture of the feedforward multibit ΔΣAD modulator for low power application. The SQNDR (Signal to Quantization Noise and Distortion Ratio) of ΔΣAD modulator is limited by the dynamic range of the input signal and non-idealities of circuit building blocks, particularly by the harmonic distortion in amplifier circuits. In a full feedforward ΔΣAD modulator structure...

The radix-22 was a milestone in the design of pipelined FFT hardware architectures. Later, radix-2 extended to radix2.However, radix-2 was only proposed for single path delay feedback (SFD) architectures, but not for feedforward, and also it called multi path delay commutator (MDC) .The radix-216 feedforward Fast Fourier Transform architecture (FFT). In feedforward architectures radix-2 can be ...

Orientation adaptation and perceptual learning change orientation tuning curves of V1 cells. Adaptation shifts tuning curve peaks away from the adapted orientation, reduces tuning curve slopes near the adapted orientation, and increases the responses on the far flank of tuning curves. Learning an orientation discrimination task increases tuning curve slopes near the trained orientation. These c...

The appearance of radix-2 was a milestone in the design of pipelined FFT hardware architectures. Later, radix-2 was extended to radix-2. However, radix-2 was only proposed for Single-path Delay Feedback (SDF) architectures, but not for feedforward ones, also called Multi-path Delay Commutator (MDC). This paper presents the radix-2 feedforward (MDC) FFT architectures. In feedforward architecture...

in this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and newton-cotesmethods with positive coefficient for the solution of linear fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. here neural network isconsidered as a part of large field called neural computing orsoft computing. we propose alearning algorithm from ...

The basic principle of feedforward noise cancellation for broadband active noise reduction is based on the availability of a reliable measurement of the noise source. Reliability is compromised in case the noise measurement is acoustically coupled to the actual active noise cancellation (ANC), as stability and performance of the feedforward compensation becomes ambiguous. This paper presents a ...

Most models of sensory processing in the brain have a feedforward architecture in which each stage comprises simple linear filtering operations and nonlinearities. Models of this form have been used to explain a wide range of neurophysiological and psychophysical data, and many recent successes in artificial intelligence (with deep convolutional neural nets) are based on this architecture. Howe...