State [Formula: see text] and state are same to text], which is called as multi-photon-addition amplified coherent (MPAACS) by us. Here, photon number operator, creation state, gain factor, an integer, respectively. We study mathematical physical properties for these MPAACSs, including normalization, component analysis, Wigner function, effective gain, quadrature squeezing, equivalent input noi...

This paper introduces a two-dimensional (2-D) processing approach for the analysis of multi-pitch speech sounds. Our framework invokes the short-space 2-D Fourier transform magnitude of a narrowband spectrogram, mapping harmonicallyrelated signal components to multiple concentrated entities in a new 2-D space. First, localized time-frequency regions of the spectrogram are analyzed to extract pi...

Long Short-Term Memory Recurrent Neural Networks are the current state-of-the-art in handwriting recognition. In speech recognition, Deep Multi-Layer Perceptrons (DeepMLPs) have become the standard acoustic model for Hidden Markov Models (HMMs). Although handwriting and speech recognition systems tend to include similar components and techniques, DeepMLPs are not used as optical model in uncons...

Yemanja is a model-based event correlation engine for multi-layer fault diagnosis. It targets complex propagating fault scenarios, and can smoothly correlate low-level network events with high-level application performance alerts related to quality of service violations. Entity models that represent devices or abstract components encapsulate entity behavior. Distantly associated entities are no...

Software agents and multi-agents systems (MAS from now on) are recognized as both abstractions and effective technologies for modelling and building complex distributed applications. However, they are still difficult to engineer. The reason is that when massive number of autonomous components interact it is very difficult to predict that the emergent organizational structure fits the system goa...

We propose a neural sequence-to-sequence model for direction following, a task that is essential to realizing effective autonomous agents. Our alignment-based encoder-decoder model with long short-term memory recurrent neural networks (LSTM-RNN) translates natural language instructions to action sequences based upon a representation of the observable world state. We introduce a multi-level alig...