Hiroshi Sukegawa

An embedded DRAM technology for high-performance NAND flash memories

An embedded DRAM using a standard NAND flash memory process has been demonstrated for the first time. This embedded DRAM without extra costly manufacturing process realizes 2.4 mm2 /Mb macro density and provides large-capacity on-chip page buffers and data caches for NAND flash memories to enhance their performances. A 32 KB DRAM buffer macro with 1.5 μm2cell has been fabricated with a 32 nm NAND flash memory process. Even with small 3 fF cell using a planar MOS capacitor, an enough ±100 mV cell signal has been obtained by introducing a technique to self-boost cell node up to 4 V using a merit of high-voltage NAND flash process, and two techniques to curtail parasitic bitline capacitance down to 60 fF at 128 wordlines per bitline. An undershoot problem of cell nodes due to unwanted plateline bounce is resolved by a two-step-rise/fall wordline scheme. Installation of dummy cell scheme to obtain a half of “1” data (not an average of “1” and “0” data) cuts out 32 KB macro size by 1.3% while suppressing mismatch to 3 mV at the grounded bitline precharge. The 32 KB test vehicle shows 90 ns random cycle time with 15 ns burst cycle time (66 Mb/s/pin). The measured characteristics of 2 × 10-18 bit error rater (BER) by soft error and 10 ms data retention at 85 °C are enough for page buffer application in a NAND flash memory. The measured active current of 32 KB macro is 7 mA at 90 ns random cycle, but only 3.2 mA at practical use of 15 ns burst with 256B page access.

Access Control System with Automatic Logging for User's Facial Information

An access control system that automatically logs in a user by his or her facial information is described. Furthermore, a method for automatically tracking logged data, based on a repetitive operation of template improvements, is shown. Face recognition is a favorable variety of biometrics for personal identification because users facial images can be captured successively from a standard video camera at a distance. Two models of the system using face recognition were tested to prevent fraud and to create automatic registration. Experimental results for a six-month test showed that the tracking capability of the method is quite practicable; the equal error rate for false rejection and false acceptance (EER) is only about one percent.