In this paper, we propose an adaptive encoding method of fixed codebook in CELP coders and implement an adaptive fixed code-excited linear prediction (AF-CELP) speech coder as a low-bit-rate extension to the 8 kbit/s CS-ACELP. The AF-CELP can be implemented at low bit rates as well as low complexity by exploiting the fact that the fixed codebook contribution to the speech signal is periodic, as is the adaptive codebook (or pitch filter) contribution. Listening tests show that the 6.4 kbit/s AF-CELP has a comparable quality to the 8 kbit/s CS-ACELP under real environmental test conditions.

An efficient algorithm for reconstructing all polyhedral 3D objects from two orthographic views is presented. Since the two-view orthographic representation of a 3D object is ambiguous, it requires a numerous amount of combinatorial searches in the process of reconstruction. Also, multiple number of solutions in contrast to the designers intention can be existed in the problem. This paper proposes a two phase algorithm to reduce the search space and to select the most plausible solution described by the given projections. First, the partially constructed objects are reconstructed from the restricted candidate faces corresponding to each area on the two-view drawings in its first phase. Then the complete objects are obtained from the partially constructed objects by adding other candidates with geometrical validity in the second phase. The algorithm performs a combinatorial search based on the face decision rules along with two heuristics. Decision rules check geometrical validity and heuristic rules enhance the search speed. In addition, the reconstruction finds the most plausible 3D object that human observers are most likely to select first among the given multiple solutions. Several examples from a working implementation are given to show the completeness of the algorithm.

This paper presents a new approach to computer image generation via three proposed methods for translating the evolution of a Petri net into fractal image synthesis. The idea is derived from the concept of fractal iteration principles in the escape-time algorithm and chaos game. The approach uses a Petri net as a powerful abstract modeling tool for fractal image synthesis via its duality, deadlock, inhibitor arc, firing sequence and marking reachability. The objective of this approach is to enhance the analysis technique of a Petri net and use it as a novel technique for fractal image synthesis. Generating fractal images via the dynamics of a Petri net allows an easy and direct proof for the similarity and correspondence between the dynamics of complex quadratic fractals by the recursive procedure of the escape-time algorithm and the state of a Petri net via a reachability problem. The reachability problem will be manipulated in terms of the dynamics of the fractal in order to generate images via three proposed methods. Validation of our approach is given by discussion and an illustration of some experimental results.

This paper describes a new system for extracting and classifying bibliography regions from the color image of a book cover. The same as all the color image processing, the segmentation of color space is an essential and important step in our system; and here HSI color space is adopted rather than RGB color space. The color space is segmented into achromatic and chromatic regions first; and the segmentation is completed after thresholding the intensity histogram of the achromatic region and the hue histogram of the chromatic region. Then text region extraction and classification follows. After detecting fundamental features (stroke width and local label width) text regions are determined by comparing smeared blocks to the original candidate image. Based on the general cover design model, text regions are classified into author region, title region, and publisher region furthermore, and a bibliography image is obtained as a result, without applying OCR. The appearance of the book is 3D reconstructed as well. In this paper, two examples are presented.

We propose a new associative memory named Multi-Winner Associative Memory (MWAM) and study its bidirectional association properties in this paper. The proposed MWAM has two processes for pattern pairs storage: storage process and recall process. For the storage process, the proposed MWAM can represent a half of pattern pair in the distributed representation layer and can store the correspondence of pattern and its representation using the upward weights. In addition, the MWAM can store the correspondence of the distributed representation and the other half of pattern pair in the downward weights. For the recall process, the MWAM can recall information bidirectionally: a half of the stored pattern pair can be recalled by receiving the other half in the input-output layer for any stored pattern pairs.

CTL (Computation Tree Logic) model checking is a formal method for design verification that checks whether the behavior of the verified system is contained in that of the requirements specification. If this check doesn't pass, the CTL model checker generates a subset of fair states which belongs to the system but not to the specification. In this letter, we present an incremental method which successively modifies the latest verification result each time the design is modified. Our incremental algorithm allows the designer to make changes in terms of addition or subtraction of fair CTL formulas, or fairness constraints on acceptable behavior from the problem statement. Then, these changes are adopted to update the set of fair states computed earlier. Our incremental algorithm is shown to be better than the current non-incremental techniques for CTL model checking. Furthermore, a conclusion supported by the experimental results is presented herein.

We propose a learning algorithm for self-organizing neural networks to form a topology preserving map from an input manifold whose topology may dynamically change. Experimental results show that the network using the proposed algorithm can rapidly adjust itself to represent the topology of nonstationary input distributions.