In an 8B/10B mode giga-bit-per-second serial data transactions, the de-serialized data is sent to a comma detection and word alignment (CDWA) module to identify the word boundaries, which is a prerequisite in the high-speed transceivers such as PCIe, USB and JESD204B/C. In order to ensure that the comma code (/K/-code) can be correctly detected. Ten 10-bit comma detector cells are adopted in a typical CDWA module, which require a complex circuitry and an enormous power consumption. To overcome these limitations, a low-area and low-power CDWA circuit for JESD204B/C transceiver chip in 8B/10B mode has been proposed in this paper. The bit width of the detector cells can be truncated from 10 to 6 under the condition, that CDWA module can detect a complete comma code correctly. On one hand, the proposed CDWA module is verified with a FPGA development platform with the reduction of the hardware resources and power consumption to 31.72% and 20.11% respectively as compared to the typical structure available. On the other hand, a 10-Gbps transceiver chip with the proposed CDWA module is fabricated with a 55-nm CMOS process and the word alignment function of the proposed module is proved by the measurement results. The area of this transceiver chip including 2× transmitting links and 2× receiving links is 2.89 mm ² , and the power consumption is 467.8 mW, under a maximum data transmission rate of 10 Gbps.

In this article, a moving accumulative sign filter (MASF) voter model and a low-power serial voting circuit are proposed for high-speed clock data recovery (CDR). Different from the previously reported parallel voter and moving average majority voter (MV), the proposed design is based on the MASF algorithm and adopts a two-stage voting structure. Only D-flip-flop (DFF) and basic logic gates are used to realize the serial voting function of the four continuous lead/lag/hold decision signals. The proposed MV realizes the signal processing of the four-phase error information without using traditional gain and quantization operations. In addition, by eliminating the redundant output state, the input noise of the digital filter of CDR can be reduced, which could also reduce the power consumption of the subsequent circuits due to less logical flips. As a result, the proposed serial MV can operate at a half baud rate in a high-speed CDR and it can reduce the chip area by removing the demultiplexer unit and the moving average filter. The proposed MV circuit is implemented for a high-speed CDR using a 40-nm CMOS process, which shows a 12-GHz maximum operating speed. The measured power consumption of the whole voter at 10 GHz is only 0.55 mW and the core chip area is 8.6 × 25.4 μm ² .

A novel down-sampling filter named moving accumulative sign filter (MASF) is proposed for low-power down-sampling of large-scale binary and ternary data. Besides, the MASF has greatly circuit realization advantages than state-of-the-art cascaded-integrator-comb (CIC) filter, especially in the area of low-power design. The theory of MASF is proposed and introduced comprehensively, including the algorithm model, transfer function, and frequency response characteristics. The pipeline voting architecture is applied to the implementation of the MASF to improve the speed of data processing, which simplifies the circuit structure and reduce the power consumption. The MASF circuits of general application based on pipeline voting are designed for binary and ternary signals only using D flip-flop and logic gates. The area and power consumption of MASF are reduced by 86% and 88% compared with CIC filter under the same conditions on FPGA. What’s more, a hardware-friendly pooling algorithm named polar-pooling is proposed based on MASF for binary and ternary feature maps, which greatly reduces the time and space complexity of pooling. Compared with max-pooling and average-pooling, the processing time of polar-pooling is reduced by more than 75% for a $200\times 200$ binary image. The two-stage MASF circuit for ternary signal processing is implemented at 40-nm CMOS process, compared with state-of-the-arts cascade-of-integrators filter which cascading two integrators, the normalized power consumption of proposed two-stage MASF circuit has 67% reduction and the area has 75% reduction.

Cyclic redundancy check (CRC) and Forward error correction (FEC) encoding are widely used in high-speed information transceiver systems such as PCIe, JESD204C and fiber-optic communications to detect or correct errors in data. Traditionally, the CRC and FEC encoding circuits in JESD204C are implemented independently of each other, which consumes a significant amount of hardware resources. Therefore, a high logic density CRC and FEC logic sharing (CFLS) encoding circuit for JESD204C controller is proposed in this paper, and the logic density of the encoding circuit is improved by sharing the registers and common encoding factor (CEF). Meanwhile, a straightforward critical path delay (CPD) calculation method was proposed to assess whether the data transmission delay satisfies the requirements of CFLS circuits. This method is derived in conjunction with the manipulation of the common factor matrix, thus reducing computational complexity. The CFLS encoding circuit proposed in this paper is verified with an FPGA platform, and the results show that the circuit can realize CRC and FEC function with a 21.96% reduction in hardware resources, compared to the traditional methods. The area of the JESD204C controller with CFLS encoding circuits is 0.09 mm2, by using a 40-nm CMOS process, and the power consumption is 24.66 mW according to the post-layout simulation.

Existing self-driving itinerary planning systems rely on single-objective optimization and static cost estimation, limiting their ability to accommodate diverse user preferences and dynamic price fluctuations. Methods: This study presents an interactive itinerary planning system formulated as a Tourist Trip Design Problem (TTDP) with subset selection, integrating an improved NSGA-II algorithm for simultaneous optimization of travel time, cost, and experiential quality, a WPGA-based combined prediction model for dynamic cost forecasting, and a human-in-the-loop interface for real-time preference adjustment. Results: Evaluated on 30 Hainan Island attractions under a 7-day/6-night scenario with 30 independent runs, the improved NSGA-II selects 8.9 ± 1.0 stops with total time 26.2 ± 4.7 h, cost CNY 1526 ± 356, and experience index 36.69 ± 5.60, with backend optimization latency 0.5 ± 0.1 s (end-to-end user-perceived latency including network and frontend rendering: 1.8 s). Compared with standard NSGA-II, the improved version achieves 114.0% higher aggregate experience index while selecting more stops (8.9 vs. 4.2); this improvement is primarily driven by the larger number of selected stops, and normalized indicators (experience per stop: 4.12 vs. 4.08) provide a more balanced interpretation of the trade-offs. The cost model covers three categories (fuel, tickets, and hotel), with the optimization objective f2 capturing route-dependent costs (fuel + tickets) and the hotel treated as a fixed baseline. However, empirical validation is restricted to two geographic corridors.