8,575 research outputs found
Achievable Angles Between two Compressed Sparse Vectors Under Norm/Distance Constraints Imposed by the Restricted Isometry Property: A Plane Geometry Approach
The angle between two compressed sparse vectors subject to the norm/distance
constraints imposed by the restricted isometry property (RIP) of the sensing
matrix plays a crucial role in the studies of many compressive sensing (CS)
problems. Assuming that (i) u and v are two sparse vectors separated by an
angle thetha, and (ii) the sensing matrix Phi satisfies RIP, this paper is
aimed at analytically characterizing the achievable angles between Phi*u and
Phi*v. Motivated by geometric interpretations of RIP and with the aid of the
well-known law of cosines, we propose a plane geometry based formulation for
the study of the considered problem. It is shown that all the RIP-induced
norm/distance constraints on Phi*u and Phi*v can be jointly depicted via a
simple geometric diagram in the two-dimensional plane. This allows for a joint
analysis of all the considered algebraic constraints from a geometric
perspective. By conducting plane geometry analyses based on the constructed
diagram, closed-form formulae for the maximal and minimal achievable angles are
derived. Computer simulations confirm that the proposed solution is tighter
than an existing algebraic-based estimate derived using the polarization
identity. The obtained results are used to derive a tighter restricted isometry
constant of structured sensing matrices of a certain kind, to wit, those in the
form of a product of an orthogonal projection matrix and a random sensing
matrix. Follow-up applications to three CS problems, namely, compressed-domain
interference cancellation, RIP-based analysis of the orthogonal matching
pursuit algorithm, and the study of democratic nature of random sensing
matrices are investigated.Comment: submitted to IEEE Trans. Information Theor
Forward Attention in Sequence-to-sequence Acoustic Modelling for Speech Synthesis
This paper proposes a forward attention method for the sequenceto- sequence
acoustic modeling of speech synthesis. This method is motivated by the nature
of the monotonic alignment from phone sequences to acoustic sequences. Only the
alignment paths that satisfy the monotonic condition are taken into
consideration at each decoder timestep. The modified attention probabilities at
each timestep are computed recursively using a forward algorithm. A transition
agent for forward attention is further proposed, which helps the attention
mechanism to make decisions whether to move forward or stay at each decoder
timestep. Experimental results show that the proposed forward attention method
achieves faster convergence speed and higher stability than the baseline
attention method. Besides, the method of forward attention with transition
agent can also help improve the naturalness of synthetic speech and control the
speed of synthetic speech effectively.Comment: 5 pages, 3 figures, 2 tables. Published in IEEE International
Conference on Acoustics, Speech and Signal Processing 2018 (ICASSP2018
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