In this brief, we introduce a priority encoder that uses a novel priority lookahead (PL) scheme to reduce delays associated with priority propagation. Two priority encoder approaches are presented, one without and the other with a PL scheme. For an -bit encoder, the circuit with the PL scheme requires about 0.1 more transistors than the circuit without the scheme. However, a 32-bit very large s...

A generic CPM scheme can be decomposed into a continuous-phase encoder (CPE) and a memoryless modulator (MM). The CPE can be combined with a channel encoder (CE). This creates an extended CE, as the CPE is now an extension of the CE. In this paper, a 1⁄2 rate quaternary CE is combined with a quaternary CPE. The CE used here is a convolutional encoder, thus, the extended CE is also a convolution...

This paper presents the design of a hardware architecture for the Entropy Encoder of H.264/AVC video compression standard, considering the baseline profile. The entropy encoder is composed by two main blocks: Exp-Golomb encoder and CAVLC encoder. This paper presents the architectural design of these two blocks. The synthesis results targeting Xilinx FPGAs showed that the Exp-Golomb and CAVLC en...

This paper presents a new method to increase the available measurement resolution of quadrature encoder signals. The proposed method features an adaptive signal correction phase and an interpolation phase. Typical imperfections in the encoder signals including amplitude difference, mean offsets and quadrature phase shift errors are corrected using recursive least squares with exponential forget...

We introduce multi-modal, attentionbased Neural Machine Translation (NMT) models which incorporate visual features into different parts of both the encoder and the decoder. Global image features are extracted using a pre-trained convolutional neural network and are incorporated (i) as words in the source sentence, (ii) to initialise the encoder hidden state, and (iii) as additional data to init...

An encoder-decoder architecture with recurrent neural networks in both the encoder and decoder is a standard approach to the question-answering problem (finding answers to a given question in a piece of text). The Dynamic Coattention[1] encoder is a highly effective encoder for the problem; we evaluated the effectiveness of different decoder when paired with the Dynamic Coattention encoder. We ...