Abstract:
Presented is a new method of extracting the feature information of speech. Kernels which represent the main frequency behavior of a base layer responding to sound is defined. Inputted speech is represented by at least one kernel among the kernels. Information about the represented kernel is used as the feature information of the inputted speech.
Abstract:
A self-reparable circuit capable of outputting a plurality of state values and restoring a 1-bit error is disclosed. This circuit comprises: a self-reparable circuit for sequentially outputting an N number of fixed values; a combination circuit for outputting a (k+1)^th fixed value when a k^th fixed value outputted from the self-reparable circuit among the N number of fixed values is input; and a circuit structure change determination circuit for selecting an internal circuit of the self-reparable circuit such that the self-reparable circuit can output the (k+1)^th fixed value when the (k+1)^th fixed value is input. [Reference numerals] (10) Coupling circuit (self-reparable circuit); (11) Combination circuit; (13) Circuit structure change determination circuit
Abstract:
Disclosed is a method for analyzing network properties including the steps of: receiving data about a network which includes nodes and links; generating data about a modified network which is modified by selecting one or more of the nodes and the links and perturbing the (original) network; and computing the data regarding one or more of a point attractor, the basin of the point attractor, a cyclic attractor, and the basin of the cyclic attractor of the modified network. [Reference numerals] (S11) Receiving the data of a boolean network having a plurality of nodes and a plurality of links for connecting the nodes; (S12) Generating data about a modified network modified from the network by perturbing the boolean network as one or more control targets selected among the nodes and the links; (S13) Calculating data about one or more things among a point attractor, a point attractor basin, a cyclic attractor, and a cyclic attractor basin in the modified network; (S14~S17) Providing the result of comparing the information about a point attractor, a point attractor basin, a cyclic attractor, or a cyclic attractor basin in the boolean network with the information about a point attractor, a point attractor basin, a cyclic attractor or a cyclic attractor basin in the modified network
Abstract:
A method of registering devices in a wireless personal area network is provided to reduce power consumption of the network by quickly registering the plural devices to the piconet by preventing collision among devices during a registering process. A piconet includes a PNC(PicoNet Coordinator)(110) and at least one device(120). The PNC is selected from FFDs(Full Function Devices) or RFDs(Reduced Function Devices). The PNC schedules the data communication in the piconet and transmits a control signal to the devices. The devices communicate with the PNC or with each other. A superframe which is delivered among the devices includes an active period and an inactive period. The active period includes a beacon period, a contention access period, and a contention free period.
Abstract:
A two-way language phone system for the recognition and generation of sign language is provided so that aurally handicapped persons can lead leisure life through a video phone system program or obtain information required for social activities or education. A two-way language phone system for the recognition and creation of sign language consists of a system processing part(100), a sign language input part(110), a sign language output part(120), a communication line part(130), and a DB group(140). The system processing part(100) comprises a sentence generation part(200), a voice generation part(400), a sentence creation part(500), and a sign language generation part(300). The sign language input part(110) recognizes a sign language operation or a sign language form through a camera and provides corresponding sign language image data to the sentence generation part(200). The sentence generation part(200) searches the sign language DB of the DB group(140) for a sentence corresponding to the sign language image data provided from the sign language input part(110). The voice generation part(400) obtains the phonemes corresponding to the sentence, provided from the sentence generation part(200), from the voice DB of the DB group(140), combines them into a voice, and provides it to the communication line part(130). The sentence creation part(500) searches the voice recognition DB of the DB group(140) for a sentence corresponding to the voice provided from the communication line part(130) and provides it to the sign language generation part(300).